tag:blogger.com,1999:blog-71201349974353936962024-03-13T03:03:23.397-07:00Magnus Ducatus Lituaniae ProjectMagnus Ducatus Lituaniae Project - BGA analysis project for the territories of former Grand Duchy of Lithuania.
Admin: Vadim Verenich
Co-admin: Leon KullProject "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.comBlogger80125tag:blogger.com,1999:blog-7120134997435393696.post-80947790613279290002012-11-15T11:55:00.002-08:002012-11-15T11:56:33.017-08:00New add-on tool to MDLP World-22 calculator<div dir="ltr" style="text-align: left;" trbidi="on">
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<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: small;"><b>Alex_Axe</b> from <a href="http://forum.molgen.org/index.php/topic,4961.msg161236.html#msg161236">Molgen forum</a> announced the release of a new tool <a href="http://db.tt/0FN1Qhpr">Oracle_AdMix4</a>.</span></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: small;">Basically, you can think of this tool as an useful add-on that extends the Oracle <i>two-population</i> results into <i>four-population</i> format.<br /><br />Currently the tool support only DOS/Windows platform, and its usage is quite straightforward. The current distribution of Oracle_AdMix4 includes the required file (<b>data.txt</b>) with the frequencies of 22 components in each of reference populations. The second file - <b>input.txt</b> - is the one you need to modify in order to use the tool on your own World-22 calculator results:<br /><br />30 {Quantity of output results}
<br />1,5 {Threshold of components to ignore noise}
<br />0,5 {Threshold of method to ignore noise}
<br />2 {Power parameter for weighted method or zero for least-squares method} <br /><b>0 Pygmy
<br />15 West-Asian
<br />0 North-European-Mesolithic
<br />0 Indo-Tibetan
<br />0 Mesoamerican
<br />0 Arctic-Amerind
<br />0 South-America_Amerind
<br />5 Indian
<br />0 North-Siberean
<br />25 Atlantic_Mediterranean_Neolithic
<br />5 Samoedic
<br />0 Indo-Iranian
<br />0 East-Siberean
<br />40 North-East-European
<br />0 South-African
<br />0 North-Amerind
<br />0 Sub-Saharian
<br />0 East-South-Asian
<br />10 Near_East
<br />0 Melanesian
<br />0 Paleo-Siberian
<br />0 Austronesian</b></span></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: small;">All you need to do is to change the default values of components with your own results of World-22 calculator.<br /><br />The output should appear in the following format:<br /><br /><i>1 Mordovian+Russian_South+Swedish+Swedish @ 20,749639<br />2 Estonian+Mordovian+Swedish+Swedish @ 23,267935<br />3 Finnish-North+Mordovian+Polish+Swedish @ 23,656645<br />4 Finnish-North+Mordovian+Russian_South+Swedish @ 23,83736<br />5 Estonian+Finnish-South+Mordovian+Swedish @ 24,192354<br />6 Mordovian+Polish+Swedish+Swedish @ 24,846391<br />7 Estonian+German-North+Mordovian+Swedish @ 25,176036<br />8 Lithuanian+Mordovian+Swedish+Swedish @ 25,511204<br />9 Finnish-North+Lithuanian+Mordovian+Swedish @ 25,523722<br />10 Finnish-South+Lithuanian_V+Mordovian+Swedish @ 25,539837</i></span></span></div>
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Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com22tag:blogger.com,1999:blog-7120134997435393696.post-83113109622590323892012-11-11T15:01:00.000-08:002012-11-15T11:29:59.187-08:00The levels and dating of admixture in Belorusians<div dir="ltr" style="text-align: left;" trbidi="on">
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<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: small;"><br /></span><span style="font-size: small;">Following Dienekes's suggestion on using Pathan and Lithuanian samples as references for ROLLOFF analysis, i decided to undertake a second attempt of formal analysis of admixture and dating of admixture events in Belorusian samples which are available to me: the reference dataset of Belorusians from <a href="http://www.nature.com/nature/journal/v466/n7303/full/nature09103.html">Behar et al.2011</a>., and Belorusian samples collected by our project.</span></span><br />
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<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: small;">Below you can glean the results of experiment which i deem less noisy in contrast to my previous attempt. </span></span><br />
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<span style="font-family: Verdana,sans-serif;"><span style="font-size: x-small;">valid snps: 746877<br />group 0 Lithuanian<br />group 1 Pathan<br />number admixed: 13 number of references: 2<br />numsnps: 746877 numindivs: 55<br />starting main loop. numsnps: 158101</span><br /><span style="font-size: x-small;"><br />Summary of fit:<br /><br />Formula: wcorr ~ (C + A * exp(-m * dist/100))<br /><br />Parameters:<br /> Estimate Std. Error t value Pr(>|t|) <br />C 2.332e-04 3.029e-04 0.770 0.44165 <br />A 3.306e-02 1.227e-02 2.695 0.00728 **<br />m 1.169e+02 3.851e+01 3.037 0.00252 **<br />---<br />Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 <br /><br />Residual standard error: 0.006508 on 493 degrees of freedom<br /><br />Number of iterations to convergence: 0 <br />Achieved convergence tolerance: 9.103e-06 <br /><br />mean (generations): 116.9416</span></span></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhzLKU0qHDD6iLQEZh-hNV5QLZOFG25rCKkEpFIfwxjRQjAXSykedEAcOVXObMBFxuT2g1HVYNjGt8m1ho8elLmXFoBaxqh2cApo84pwm2uZmc_fG1sghEZuCW4EFD9UpySZn930v_58AI/s1600/LithPathan.gif" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhzLKU0qHDD6iLQEZh-hNV5QLZOFG25rCKkEpFIfwxjRQjAXSykedEAcOVXObMBFxuT2g1HVYNjGt8m1ho8elLmXFoBaxqh2cApo84pwm2uZmc_fG1sghEZuCW4EFD9UpySZn930v_58AI/s320/LithPathan.gif" width="319" /></a></div>
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<span style="font-family: Verdana,sans-serif;"><span style="font-size: x-small;"><b>jackknife</b><span style="font-size: x-small;"><b> </b><span style="font-size: x-small;"><b>(generations) 105.086<span style="font-size: x-small;">+-</span>52.591</b></span></span><span style="font-size: small;"> </span></span></span><br />
<span style="font-family: Verdana,sans-serif;"><span style="font-size: x-small;"><span style="font-size: small;">The date of admixture event in Belarusian_V sample with Belarusian and Pathan being reference populations appears to be very close to the date which was estimated by Dienekes for Lithuanian [Lithuanian_D;Pathan].</span></span></span></div>
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<span style="font-family: Verdana,sans-serif;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-family: "Trebuchet MS",sans-serif;"><br /></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span>
<span style="font-family: Verdana,sans-serif;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-family: "Trebuchet MS",sans-serif;"><b><span style="font-size: small;">Inference of Admixture Parameters in Belarusians using Weighted Linkage Disequilibrium</span></b></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span><br />
<span style="font-family: Verdana,sans-serif;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-family: "Trebuchet MS",sans-serif;"></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span><br />
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<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: small;">On 1 November 2012 Po-Ru Loh, Mark Lipson, Nick Patterson, Priya Moorjani, Joseph K Pickrell, David Reich, Bonnie Berger announced and published their new <a href="http://arxiv.org/abs/1211.0251">paper</a>, in which they introduced a new approach that harnesses the exponential decay of
admixture-induced linkage disequilibrium (LD) as a function of genetic
distance. They proposed </span><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: small;"> a new weighted LD statistic that can be used to infer mixture proportions
as well as dates with fewer constraints on reference populations than
previous methods.</span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"><span style="font-size: x-small;"> <br /><br /><br /><span style="font-size: x-small;"><span style="font-size: small;">I haven't had enough time to investigate </span><span style="font-size: x-small;"><span style="font-size: small;">t</span><span style="font-size: x-small;"><span style="font-size: small;">his method in full extent, but i used </span><span style="font-size: x-small;"><span style="font-size: small;">a </span><span style="font-size: x-small;"><span style="font-size: small;">software package ALD</span><span style="font-size: x-small;"><span style="font-size: small;">er</span><span style="font-size: x-small;"><span style="font-size: small;"> which </span><span style="font-size: x-small;"><span style="font-size: small;">im</span><span style="font-size: x-small;"><span style="font-size: small;">plements </span><span style="font-size: x-small;"><span style="font-size: small;">the </span><span style="font-size: x-small;"><span style="font-size: small;">weighted LD stat</span><span style="font-size: x-small;"><span style="font-size: small;">i</span><span style="font-size: x-small;"><span style="font-size: small;">stic for a quick </span><span style="font-size: x-small;"><span style="font-size: small;">& dirty </span><span style="font-size: x-small;"><span style="font-size: small;">ex</span><span style="font-size: x-small;"><span style="font-size: small;">periment </span><span style="font-size: x-small;"><span style="font-size: small;">of dating the admixture </span><span style="font-size: x-small;"><span style="font-size: small;">events</span><span style="font-size: x-small;"><span style="font-size: small;"> in Belaru<span style="font-size: small;">sian sample</span>:</span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiunBvx1o3d42zUvadzQiadESJItcQU-S6uM-2yKAWyC6YCCLaDT7buQbp1o5wH7-PiWBUTIFoVF8GImPd75tMTFVM4iF0BChn1jMr92_ecf6GZgM3tQSyhmN2YmrwG8mxXz5FTSaq-HYo/s1600/Beladmixture.gif" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="207" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiunBvx1o3d42zUvadzQiadESJItcQU-S6uM-2yKAWyC6YCCLaDT7buQbp1o5wH7-PiWBUTIFoVF8GImPd75tMTFVM4iF0BChn1jMr92_ecf6GZgM3tQSyhmN2YmrwG8mxXz5FTSaq-HYo/s320/Beladmixture.gif" width="320" /></a></div>
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Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com0tag:blogger.com,1999:blog-7120134997435393696.post-50111935025356408212012-10-14T14:23:00.000-07:002012-10-14T14:24:51.190-07:00ROLLOFF analysis of Poles, Belarusians and Russians from central regions of Russia<div dir="ltr" style="text-align: left;" trbidi="on">
<span style="font-family: "Trebuchet MS",sans-serif;">A month ago the notorious Reich lab released an <a href="http://genetics.med.harvard.edu/reich/Reich_Lab/Software.html">alpha version of ADMIXTOOOLS version 1.0.</a> The alpha version package was developed for i<i>n-house</i> use, so the operating routine is not always self-explanatory. The goof thing, however, is that ADMIXTOOLS package maintains full format compatibility with another very well-known EIGENSOFT software program developed by the same lab. This makes the learning curve of ADMIXTOOLS much steeper and flatter. </span><br />
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<span style="font-family: "Trebuchet MS",sans-serif;">The aforementioned package features 6 cool programs, among which i find most useful <b>qp3Pop</b> and <b>rolloff</b>. Due to limitations of this post, i am not going to discuss qp3pop in all details and for the purpose of my presentation it is suffice to say that this program implements three- population (f_3) test for treeness of populations from <a href="http://www.nature.com/nature/journal/v461/n7263/abs/nature08365.html" rel="nofollow">Reich et al. 2009</a></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">Rather i'd suggest reading ADMIXTOOLS supporting material, Dienekes' posts and Reich's paper to get an idea of what f_3 test is about.</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">ROLOFF method, however, needs a closer look.This is a method that measures time since admixture. It does so by looking at the linkage disequilibrium between SNPs due to admixture. Now it is time to recall the standard definition of the linkage disequilibrium. The linkage disequilibrium (further -<b>LD</b>) is the nonrandom association between two alleles such that certain combinations are more likely to occur together. As two SNPs get farther apart, we expect there to be less admixture LD.The rate of decline of admixture LD is directly related to the number of generations since admixture, since that indicates how many recombinations have occurred between any two SNPs. In short: <b>Rolloff fits an exponential curve to a plot of admixture LD vs. distance, and uses the rate of exponential decline to calculate the generations since admixture. </b>Given that one generation is roughly equal to 29 years, one can convert the number of generations since admixture into years.</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">Dienekes has already tested ADMIXTOOLS programs with various worldwide populations, and among other he has carried out f_3 and rolloff analyses of Poles, Lithuanians, and Ukrainians.</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">Below are words from the man himself:</span></div>
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<span style="font-size: x-small;"><span style="font-family: "Trebuchet MS",sans-serif;">Using the aforementioned idea, I set out to see whether <b>Lithuanians</b>, who
occupy the European end of the Europe-South Asia cline present such a
signal of admixture LD. I used the Lithuanian_D sample from the Dodecad
Project and the Balochi HGDP sample as reference populations (to
calculate allele frequency differences), and the Behar et al. (2010)
Lithuanians for admixture LD. There were only ~300k SNPs usuable in this
set, but sufficient to detect the signal of admixture LD:</span></span></div>
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<span style="font-size: x-small;"><span style="font-family: "Trebuchet MS",sans-serif;">The admixture time estimate is <b>200.350 +/- 61.608</b> generations, or <b>5,810 +/- 1790</b> years.
This is not very precise, probably because of the small number of SNPs
and individuals used, but it certainly points to the Neolithic-to-Bronze
Age for the occurrence of this admixture. The date is certainly
reminiscent of the expansion of the Kurgan culture out of eastern
Europe, or, the later Corded Ware culture of northern Europe.<br /><br />
So, it may well appear that at least some of the people participating in
these groups of cultures, were indeed influenced by the Indo-Europeans
as they expanded from their West Asian homeland. These intruders mixed
with eastern Europeans who vacillated during the late Neolithic between a
northern Europeoid pole akin to Mesolithic hunter gatherers from </span>
<span style="font-family: "Trebuchet MS",sans-serif;"><a href="http://dienekes.blogspot.com/2012/04/ancient-dna-from-neolithic-sweden.html">Gotland</a> and <a href="http://dienekes.blogspot.com/2012/06/mesolithic-iberians-la-brana-arintero.html">Iberia</a>,
and a widely dispersed Sardinian-like population that is in evidence at
least in the Sweden-Italian Alps-Bulgaria triangle. The gradual <a href="http://dienekes.blogspot.com/2012/07/population-strata-in-west-siberian.html">appearance</a> of non-mtDNA U related lineages in Siberia and Ukraine is most likely related to this phenomenon.</span></span></div>
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<span style="font-size: x-small;"><span style="font-family: "Trebuchet MS",sans-serif;">I have carried out <i>rolloff </i>analysis of my 25-strong <b>Polish_D sample</b> using Lithuanians and Pathans as references:</span></span></div>
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<span style="font-size: x-small;"><span style="font-family: "Trebuchet MS",sans-serif;">The signal is fairly distinct, and corresponds to <b>149.296 +/- 38.783</b> generations or <b>4330 +/- 1120 years</b>.
I am guessing that either the different reference population (Pathans
vs. Balochi), or, more likely the increased number of target individuals
(25 vs. 10) have contributed to the narrowing down of the uncertainty.
It will be interesting to explore this signal further with more
population pairs.</span></span></div>
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<span style="font-size: x-small;"><span style="font-family: "Trebuchet MS",sans-serif;">... </span></span></div>
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<span style="font-size: x-small;"><span style="font-family: "Trebuchet MS",sans-serif;">I have used the Yunusbayev et al. sample of <b>Ukrainians</b>, and estimated
its admixture time using Lithuanians and Balochi as reference
populations: The admixture time estimate is <b>191.078 +/- 35.079</b> generations, or <b>5,540 +/- 1,020 years</b>.
It seems very similar to that in Lithuanians, with a smaller standard
error, perhaps on account of either the larger number of SNPs or larger
number of individuals.<br /><br />
It is tempting to associate this admixture signal with the </span>
<span style="font-family: "Trebuchet MS",sans-serif;"><a href="http://en.wikipedia.org/wiki/Maikop_culture">Maikop culture</a>
which appeared at around this time. Assuming that
North_European/West_Asian (or Lithuanian-like and Balochi-like) gene
pools existed north and south of the Pontic-Caspian-Caucasus set of
geographical barriers, then the Maikop culture which shows links to both
the early Transcaucasian culture and those of Eastern Europe would have
been an ideal candidate region for the admixture picked up by <i>rolloff </i>to have taken place. There are, of course, other possibilities.</span></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">As always, Dienekes' analysis spawned a lot of criticism on behalf of another genome blogger - Davidski from Eurogenes. In his latest post he argued that </span><span style="font-size: 100%;"><span style="font-family: arial;">it’s
difficult to say what this experiment was testing exactly because
Pathans aren’t pure West Asians and Lithuanians aren’t pure Mesolithic
Europeans. He also claimed that Dienekes' interpretations are wrong<i>, because </i></span></span><span style="font-size: 100%;"><span style="font-family: arial;"><i>f3</i>-statistics and <i>rolloff</i> tests are basically picking up (belated) signals of the Mesolithic and Neolithic peopling of Europe.</span></span></div>
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<span style="font-size: 100%;"><span style="font-family: arial;">Since the aforementioned populations have the strongest presence in my dataset, and there is no consensus-opinion between genome bloggers on how to interpret the ADMIXTOOLS i've decided to put my 5 cents and to test ADMIXTOOLS.</span></span></div>
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<span style="font-size: 100%;"><span style="font-family: arial;">For the purposes of this analysis, i created ad-hoc dataset, which includes 750 000 snps samples in 250 worldwide populations. Next, i made 3*62 000 trios in the following form (X,Y; Z), where X and Y are two paired reference populations, and Z is one of three populations - central Russians, Poles and Belarusians. After that i carried out q3Pop analysis of those trios.</span></span></div>
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<span style="font-size: 100%;"><span style="font-family: arial;">From the obtained results I have picked up only those with significant negative Z-score:</span></span></div>
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<span style="font-size: 100%;"><span style="font-family: arial;"><b>Poles: </b></span></span></div>
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<span style="font-size: 100%;"><span style="font-family: arial;">X Y Z </span></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: 100%;">Estonian Jew-Iraqi Polish -0.002039 0.000179 -11.368<br />Jew-Iraqi Estonian Polish -0.002039 0.000179 -11.368<br />Italian-North Latvian Polish -0.001211 0.000109 -11.098<br />Latvian Italian-North Polish -0.001211 0.000109 -11.098<br />Estonian Italian-North Polish -0.001023 0.000093 -11.037<br />Italian-North Estonian Polish -0.001023 0.000093 -11.037<br />Estonian Jew-Iran Polish -0.001861 0.000172 -10.831<br />Jew-Iran Estonian Polish -0.001861 0.000172 -10.831<br />Armenian Estonian Polish -0.001425 0.000136 -10.505<br />Estonian Armenian Polish -0.001425 0.000136 -10.505<br />Italian-South Latvian Polish -0.001344 0.000129 -10.458<br />Latvian Italian-South Polish -0.001344 0.000129 -10.458<br />Cypriot Estonian Polish -0.001626 0.000161 -10.113<br />Estonian Cypriot Polish -0.001626 0.000161 -10.113<br /> </span></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: 100%;"><b>Russians_Central</b></span></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: 100%;">North_Amerind Sardinian Russian_Center -0.004202 0.000479 -8.779<br />Sardinian North_Amerind Russian_Center -0.004202 0.000479 -8.779<br />Basque Ket Russian_Center -0.003771 0.000444 -8.493<br />Ket Basque Russian_Center -0.003771 0.000444 -8.493<br />Karitiana Sardinian Russian_Center -0.005947 0.000704 -8.453<br />Sardinian Karitiana Russian_Center -0.005947 0.000704 -8.453<br />Pima Sardinian Russian_Center -0.004908 0.000605 -8.117<br />Sardinian Pima Russian_Center -0.004908 0.000605 -8.117<br />Ket Sardinian Russian_Center -0.004295 0.000552 -7.786<br />Sardinian Ket Russian_Center -0.004295 0.000552 -7.786<br />Lithuanian Oroqen Russian_Center -0.00344 0.000445 -7.731<br />Oroqen Lithuanian Russian_Center -0.00344 0.000445 -7.731<br />Basque Karitiana Russian_Center -0.004629 0.000609 -7.596<br />Karitiana Basque Russian_Center -0.004629 0.000609 -7.596<br />Basque Pima Russian_Center -0.003711 0.000492 -7.545<br />Pima Basque Russian_Center -0.003711 0.000492 -7.545</span></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: 100%;">North_Amerind Sardinian Russian_Center -0.003465 0.000462 -7.505<br />Sardinian North_Amerind Russian_Center -0.003465 0.000462 -7.505<br />Basque Nganassan Russian_Center -0.003574 0.000478 -7.471<b> </b></span></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: 100%;"><b>Belarusians</b></span></span><br />
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<span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: "Trebuchet MS",sans-serif;">Indian Polish Belarusian -0.000736 0.000251 -2.935<br />Polish Indian Belarusian -0.000736 0.000251 -2.935<br />Karitiana Sardinian Belarusian -0.001278 0.000517 -2.471<br />Sardinian Karitiana Belarusian -0.001278 0.000517 -2.471<br />Otzi North_Amerind Belarusian -0.002556 0.001126 -2.271<br />Cirkassian Polish Belarusian -0.000488 0.000231 -2.113<br />Polish Cirkassian Belarusian -0.000488 0.000231 -2.113<br />Pima Otzi Belarusian -0.002727 0.00137 -1.99<br />Pima Sardinian Belarusian -0.000794 0.000431 -1.843<br />Sardinian Pima Belarusian -0.000794 0.000431 -1.843<br />Otzi Surui Belarusian -0.002938 0.001931 -1.522<br />Surui Otzi Belarusian -0.002938 0.001931 -1.522</span><b><span style="font-family: "Trebuchet MS",sans-serif;"><br /> Discussion</span></b></span></span><br />
<span style="font-size: 100%;"><span style="font-family: arial;"><b></b></span></span><br />
<br />
<span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: "Trebuchet MS",sans-serif;">As it looks at first glance,the results of my ad-hoc experiment with 3qPop seems to be consistent with the findings in <a href="http://www.genetics.org/content/early/2012/09/06/genetics.112.145037.abstract">Patterson et al.2012 paper</a>: "</span></span></span><i><span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: "Trebuchet MS",sans-serif;">the most striking finding is a clear signal of admixture into northern Europe, with one
ancestral population related to present day Basques and Sardinians, and
the other related to present day populations of northeast Asia and the
Americas. This likely reflects a history of admixture between Neolithic
migrants and the indigenous Mesolithic population of Europe, consistent
with recent analyses of ancient bones from Sweden and the sequencing of
the genome of the Tyrolean ‘Iceman’".</span></span></span></i><br />
<i><span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: "Trebuchet MS",sans-serif;"></span></span></span></i><br />
<br />
<span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: "Trebuchet MS",sans-serif;">I</span></span></span><span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: "Trebuchet MS",sans-serif;">ndeed, the admixture in Poles can be shown as the admixture between Neolithic + Mesolithic populations of Europe, Russians/Belarusians can be represented as admixture between the ancestral population of modern populations of NE-Asia/Amerinds and Neolithic populations of Europe.</span></span></span><i><span style="font-size: 100%;"><span style="font-family: arial;"></span></span></i><br />
<i><span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: "Trebuchet MS",sans-serif;"></span></span></span></i><span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: "Trebuchet MS",sans-serif;">However, more careful examination of results allows me to reveal the additional signals of admixtures in two of three target populations - Poles and Belarusians.</span></span></span><br />
<span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: "Trebuchet MS",sans-serif;">Although its is perfectly possible to treat Estonians and Latvians as modern day proxies for the NE-populations of Mesolithic Europe, it is also obvious that these populations could have (at least in theory) the significant genetic legacy related to Baltic branch of Indo-European <a href="http://en.wikipedia.org/wiki/Corded_Ware_culture">Corded Ware culture. </a>On other hand, the second component of admixture in Poles itself is a product of admixture between Near-East/Anatolian-like Neolithic populations and more recent genetic stratum, which is probably related to the massive migration of R1b people (the ancestors of 'Bell beakers') from NE-Asia to Western Europe.</span></span></span><br />
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<span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: "Trebuchet MS",sans-serif;">Given that, i'd suggest to rewrite the components of admixtures in Poles in the following manner:</span></span></span><br />
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<b><span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: "Trebuchet MS",sans-serif;">Pole=(Neolithic_populations of Europe)+"Bell Beakerish-like")+(Mesolithic_poplations)+"Corded_Ware" component) [1]</span></span></span></b></div>
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<span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: "Trebuchet MS",sans-serif;">In Belarusians, the sources of signals of additional admixture are less clear and vague.</span></span></span></div>
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<span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: "Trebuchet MS",sans-serif;">As was shown earlier, in terms of formal admixture analysis (f3 statistics), Belarusians could be represented as the admixture between Poles and Indian/Cirkassian. The first component of admixture is already known (see above [1]), the second one, according to results, must resemble the component, common to both <b>Indian and Circkassian</b>. From the history textbooks i've learned that the territory of modern Karachay-Cherkessia was occupied in the 1st millenium AD by the Alans, or the Alani, who were a group of <b>Sarmatian</b> tribes, nomadic pastoralists of the 1st millennium AD who spoke an Eastern Iranian language which derived from Scytho-Sarmatian and which in turn evolved into modern Ossetian. The only currently known most recent ancestral population to modern Alans and modern Indians is Scytho-Sarmatian metapopulation.</span></span></span></div>
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<br /></div>
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<span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: "Trebuchet MS",sans-serif;">Thus, we can re-write the admixture formula for Belarusians in the following manner</span></span></span></div>
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<br /></div>
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<b><span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: "Trebuchet MS",sans-serif;">Belarusian=((Neolithic_populations of Europe)+"Bell Beakerish-like")+(Mesolithic_poplations)+"Corded_Ware" component)) + Scytho-Sarmatian-like</span></span></span></b></div>
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<span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: "Trebuchet MS",sans-serif;">Now, after long discussion, it is time for the admixture_dating fun!</span></span></span></div>
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<b><span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: "Trebuchet MS",sans-serif;">Admixture dating with ROLLOFF</span></span></span></b></div>
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<span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: "Trebuchet MS",sans-serif;">To estimate the admixture date in Polish population, i used as reference populations <b>Latvian and North-Italian</b></span></span></span></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgyBvIjsxlKceRd1VPFvXcYK9a3FO3PJMYppu8n2gsjgfy1j88rXpewp-0lG32oWem47oxpuSbh4ggkny9JGmYelj5AQ5lho60QoJ1fOAM_Fyg4XYbWR8rDSyiau0Ijpu68zZQqHJli770/s1600/polish-expfit.gif" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="315" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgyBvIjsxlKceRd1VPFvXcYK9a3FO3PJMYppu8n2gsjgfy1j88rXpewp-0lG32oWem47oxpuSbh4ggkny9JGmYelj5AQ5lho60QoJ1fOAM_Fyg4XYbWR8rDSyiau0Ijpu68zZQqHJli770/s320/polish-expfit.gif" width="320" /></a></div>
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<span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: "Trebuchet MS",sans-serif;"><b>The admixture date is 119.670+-37.145 generations ago, which corresponds to 3470 +-1077 years before present, or 1510 +- 1077 AD. </b>The upper limits of our dating for the admixture event seem to overlap with the timescale of<b> Unetice culture</b>. The Bronze Age in Poland, as well as elsewhere in central Europe, begins with the innovative Unetice culture, in existence in Silesia and a part of Greater Poland during the first period of this era, that is from before 2200 to 1600 BC. This settled agricultural society's origins consisted of the conservative traditions <b>inherited from the Corded Ware populations</b> and dynamic elements of the<b> Bell-Beaker people</b>. Significantly, the Unetice people cultivated contacts with the highly developed cultures of the <b>Carpathian Basin, through whom they had trade links with the cultures of early Greece.</b> Their culture also echoed inspiring influence coming all the way from the most highly developed at that time civilizations of <b>the Middle East. </b></span></span></span></div>
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<span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: "Trebuchet MS",sans-serif;">To estimate admixture date in Belarusian population, i used as reference populations <b> Polish and Indian (note: i also lowered genetic distance threshold in ROLLOFF parameters to reduce noise from more recent admixtures)</b></span></span></span><br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhDXyghrndPYgH_dPWpkW_chymxL4yLUwggYMMEyaG9nLLEIKl8P52uIyLSaUSvvmAhPG1_EvAI5pp0vIDr_RRujsv3AhCa7nhH_KMxzkSzNy5mrjlRycu6k-S69WoVaVn8h7KnZgOGjjo/s1600/belarus.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="319" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhDXyghrndPYgH_dPWpkW_chymxL4yLUwggYMMEyaG9nLLEIKl8P52uIyLSaUSvvmAhPG1_EvAI5pp0vIDr_RRujsv3AhCa7nhH_KMxzkSzNy5mrjlRycu6k-S69WoVaVn8h7KnZgOGjjo/s320/belarus.png" width="320" /></a></div>
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<span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: "Trebuchet MS",sans-serif;">As you can see, the signal of admixture is less detectable<b>, </b>and by virtue of that the margins of error in admixture dating are significantly higher than in previous example: <b>154.158+-87.024 generations ago (or, 4470 +-2523 years before present/2510 -+2523 years AD).</b></span></span></span><br />
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Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com5tag:blogger.com,1999:blog-7120134997435393696.post-44579397461365745772012-10-13T15:50:00.001-07:002012-10-14T02:53:25.445-07:00World-22 dataset: fastIBD analysis<div dir="ltr" style="text-align: left;" trbidi="on">
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<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: small;"> Various methods for detecting IBD, including
those implemented in the software programs <a href="http://www.sciencedirect.com/science/article/pii/S0002929711000115">fastIBD</a>, <a href="http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&cad=rja&ved=0CCoQFjAB&url=http%3A%2F%2Fwww1.cs.columbia.edu%2F~gusev%2Fgermline%2F&ei=zcZ5UJOKD8X74QT77YGIDA&usg=AFQjCNHbuvvJqjJ6_YxOkmYBFP55QQopeg">GERMLINE</a>, <a href="http://www.maths.bris.ac.uk/~madjl/finestructure/chromopainter_info.html">Chromopainter</a> have been developed
in the past several years using population genotype data from microarray platforms.
Now, next-generation DNA sequencing data is becoming increasingly available, enabling
the comprehensive analysis of genomes, including identifying rare variants. These
sequencing data may provide an opportunity to detect IBD with higher resolution than
previously possible, potentially enabling the detection of disease causing loci that
were previously undetectable with sparser genetic data. </span></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: small;"><a href="http://www.sciencedirect.com/science/article/pii/S0002929711000115">fastIBD</a> is a fast and computationally efficient method for detecting the identity by descent.</span>The fastIBD algorithm starts by sampling a fixed number of haplotype
pairs (four pairs by default) for each individual from the posterior
haplotype distribution. Each sampled haplotype corresponds to a sequence
of hidden Markov model (HMM) states. The fastIBD algorithm searches for
pairs of sampled haplotypes sharing the same sequence of HMM states for
a set of consecutive markers. If the pair of sampled haplotypes belongs
to two distinct individuals, the shared haplotype tract is recorded.
For each pair of individuals, overlapping shared haplotype tracts are
merged, and the merged shared haplotype tract is a mosaic of pairs of
sampled haplotype. The method has been implemented in <a href="http://faculty.washington.edu/browning/beagle/beagle.html">BEAGLE</a>, a very popular genetic analysis software. </span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: small;">The <span style="font-size: small;">s</span>imilar IBD analyses <span style="font-size: small;">have been already carr<span style="font-size: small;"><span style="font-size: small;">ied out by <span style="font-size: small;">other <span style="font-size: small;">genome <span style="font-size: small;">bloggers<span style="font-size: small;">.</span></span></span></span></span></span></span></span></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;">Dienkes Pontikos<a href="http://dodecad.blogspot.com/search/label/fastIBD"> has perfo<span style="font-size: small;">rmed different <span style="font-size: small;">fastIBD analyses </span></span></a> <span style="font-size: small;">for de<span style="font-size: small;">tecting </span></span></span></span></span></span></span></span></span></span></span><span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;">the degree of sharing<span style="font-size: small;"> between various Euro<span style="font-size: small;">asian and African <span style="font-size: small;">groups. <span style="font-size: small;">Davidski of Eurogenes project has also used fastIB<span style="font-size: small;">D method in h<span style="font-size: small;">is <a href="http://bga101.blogspot.com/2012/08/intra-european-fastibd-chromosome.html">Intr<span style="font-size: small;">a-European <span style="font-size: small;">chromosome paintings.</span></span></a></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;">Insp<span style="font-size: small;">ired by those analyses </span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span><span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: small;"> i
decided to run <span style="font-size: small;">I<span style="font-size: small;">BD sharing</span></span> analysis of World 22 calculator dataset using robust
and powerful fastIBD software (with <span style="font-size: small;">increased <span style="font-size: small;">IBD detection thresh<span style="font-size: small;">o<span style="font-size: small;">ld)</span></span></span> a<span style="font-size: small;">nd <a href="https://gist.github.com/1348796">ibd2segment sc<span style="font-size: small;">ript.</span></a></span></span></span></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: small;">I <span style="font-size: small;">have created a<span style="font-size: small;">d-h<span style="font-size: small;">oc subset of <span style="font-size: small;">var<span style="font-size: small;">ious East-European po<span style="font-size: small;">pulations by</span></span></span></span></span></span></span></span> includ<span style="font-size: small;">ing </span>samples from <span style="font-size: small;">the following populations:</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"> </span></span></span></span>
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<td align="LEFT" height="16" width="87">Mordovian</td>
</tr>
<tr>
<td align="LEFT" height="16">Sorb</td>
</tr>
<tr>
<td align="LEFT" height="16">Hungarian</td>
</tr>
<tr>
<td align="LEFT" height="16">Belarusian</td>
</tr>
<tr>
<td align="LEFT" height="16">Tatar</td>
</tr>
<tr>
<td align="LEFT" height="16">Lithuanian</td>
</tr>
<tr>
<td align="LEFT" height="16">Polish</td>
</tr>
<tr>
<td align="LEFT" height="16">Bosnian</td>
</tr>
<tr>
<td align="LEFT" height="16">Ukrainian</td>
</tr>
<tr>
<td align="LEFT" height="16">Slovakian</td>
</tr>
<tr>
<td align="LEFT" height="16">Nogai</td>
</tr>
<tr>
<td align="LEFT" height="16">Serbian</td>
</tr>
<tr>
<td align="LEFT" height="16">Estonian</td>
</tr>
<tr>
<td align="LEFT" height="16">German</td>
</tr>
<tr>
<td align="LEFT" height="16">Swedish</td>
</tr>
<tr>
<td align="LEFT" height="16">Macedonian</td>
</tr>
<tr>
<td align="LEFT" height="16">Latvian</td>
</tr>
<tr>
<td align="LEFT" height="16">Moldavian</td>
</tr>
<tr>
<td align="LEFT" height="16">Montenegrin</td>
</tr>
<tr>
<td align="LEFT" height="16">Bulgarian</td>
</tr>
<tr>
<td align="LEFT" height="16">NorthOssetian</td>
</tr>
<tr>
<td align="LEFT" height="16">Kazakh</td>
</tr>
<tr>
<td align="LEFT" height="16">Slovenian</td>
</tr>
<tr>
<td align="LEFT" height="16">Uzbek</td>
</tr>
<tr>
<td align="LEFT" height="16">Adygei</td>
</tr>
<tr>
<td align="LEFT" height="16">Armenian</td>
</tr>
<tr>
<td align="LEFT" height="16">British</td>
</tr>
<tr>
<td align="LEFT" height="16">Czech</td>
</tr>
<tr>
<td align="LEFT" height="16">Orcadian</td>
</tr>
<tr>
<td align="LEFT" height="16">Russian</td>
</tr>
<tr>
<td align="LEFT" height="16">Turk</td>
</tr>
</tbody>
</table>
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<div style="text-align: justify;">
<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"> I have calcula<span style="font-size: small;">ted <span style="font-size: small;">the s<span style="font-size: small;">um of IBD shared segments<span style="font-size: small;"> (measured in cM - centimorgans)<span style="font-size: small;">. T<span style="font-size: small;">he obtain<span style="font-size: small;">ed <span style="font-size: small;">matrix of pairw<span style="font-size: small;">ise sharing</span> <span style="font-size: small;">has been visual<span style="font-size: small;">ized in the following <span style="font-size: small;">heat maps<span style="font-size: small;">. <span style="font-size: small;">The p<span style="font-size: small;">opulations in the </span>first heat map <span style="font-size: small;">a<span style="font-size: small;">re clustered according to <span style="font-size: small;">z-score values: </span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span><span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;">high values indicate a high degree of IBD sharing, while low values indicate a low degree of IBD sharing.</span></span></span> </span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"> </span> </span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"> In <span style="font-size: small;">t</span>he second <span style="font-size: small;">heat map, a tree-like <span style="font-size: small;">h<span style="font-size: small;">ierarchic<span style="font-size: small;"> <span style="font-size: small;">grou<span style="font-size: small;">ping of pop<span style="font-size: small;">ulation is tied to the <span style="font-size: small;">total value of cM in segments shared<span style="font-size: small;"> <span style="font-size: small;">by two populations in pairwise-s<span style="font-size: small;">haring<span style="font-size: small;">.</span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhR8PdS1fQSFG3ox36eSMdvnd1TO-htnqAr6hD8RbaPHT34cZSy2kPGWAotaJIdltxwz2UDFe0U2JoyxanGY6G_EBsnhYj29Ay2N7qwsu4ip0Wv7np5vWXjw5zC7aDeUNmzxVkxqBaKeMA/s1600/heatmap2.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="544" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhR8PdS1fQSFG3ox36eSMdvnd1TO-htnqAr6hD8RbaPHT34cZSy2kPGWAotaJIdltxwz2UDFe0U2JoyxanGY6G_EBsnhYj29Ay2N7qwsu4ip0Wv7np5vWXjw5zC7aDeUNmzxVkxqBaKeMA/s640/heatmap2.png" width="640" /></a></div>
<div style="text-align: justify;">
<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"><br /></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span> I've also made so<span style="font-size: small;">me visualizations of IBD s<span style="font-size: small;">haring for selected <span style="font-size: small;">E<span style="font-size: small;">ast-European <span style="font-size: small;">populations</span></span></span></span></span></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEii5UxH8I2WvLyQuXTiE4iKjvYpneW3MzdwohI9uhyphenhyphenh5LbDTUcm8LlNjBO33O6LEn55Bt8u_lzY2iKL7OopvyA3OQlE7E5DQT1xjW6JW6RRDqWN1JQ8q1723zUfSMbTCWTy8LcdAqrz2UI/s1600/polish.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEii5UxH8I2WvLyQuXTiE4iKjvYpneW3MzdwohI9uhyphenhyphenh5LbDTUcm8LlNjBO33O6LEn55Bt8u_lzY2iKL7OopvyA3OQlE7E5DQT1xjW6JW6RRDqWN1JQ8q1723zUfSMbTCWTy8LcdAqrz2UI/s320/polish.png" width="256" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhcAV5mwU1v8sgMQUAh4Br4WoKi3LhG6ZGTANduSHrn5_1WyIeliMI2giWxExSll0ro0wvdcQ_dQ2ndglO5Y0DOLZZqxUerj3FXc1T1lo9BGZW6oxM3QMPOb_BEBIwYcfR14THekWwsBK0/s1600/serbian.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><br /></a></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><span style="font-size: small;"><span style="font-size: small;"><span style="font-size: small;"> UPDATE <span style="font-size: small;">I<span style="font-size: small;">: <span style="font-size: small;"> I<span style="font-size: small;">'ve uploaded <a href="https://docs.google.com/spreadsheet/ccc?key=0Aqn7iMc2P-yQdFZtQmlsaGlaaGd0dTZjVkJQQU1zMGc">a spreadsheet</a> with IBD <span style="font-size: small;">pairwise-sharing values to GoogleDrive.</span></span></span></span></span></span></span></span></span> </div>
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Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com1tag:blogger.com,1999:blog-7120134997435393696.post-4717738183388546002012-10-07T07:26:00.002-07:002012-10-07T07:26:11.228-07:00Spatial Analysis of Ancestry (UPDATE)<div dir="ltr" style="text-align: left;" trbidi="on">
<span style="font-family: "Trebuchet MS",sans-serif;">One member of my project (known as "linkus") has created a map (on Google Maps) <a href="https://maps.google.com/maps/ms?msid=213246973531676142115.0004cae72024ef4d4ef6b&msa=0">with the inferred coordinates of 'ancestral locations of the MDLP participants' being superimposed on the geographic map of Europe.</a></span><br />
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<a href="http://uploadpic.org/storage/2011/27oy1bkuoGFjbCFtAPdZPKn6j.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="184" src="http://uploadpic.org/storage/2011/27oy1bkuoGFjbCFtAPdZPKn6j.png" width="320" /></a></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">Last but mot least i feel obliged to mention a couple of dendrographs by courtesy of another enthusiastic member of our project ( this guy goes by codename: "Wojewoda").</span><br />
<span style="font-family: "Trebuchet MS",sans-serif;">These 'dendrographs' aim to visualize the geneographical distance between the MDLP participants, and by virtue of that they are worth noticing.</span><br />
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<a href="http://uploadpic.org/storage/2011/u3Km6FtsuW6smWDTxKqJIrAI.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="181" src="http://uploadpic.org/storage/2011/u3Km6FtsuW6smWDTxKqJIrAI.png" width="320" /></a></div>
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<a href="http://imageshack.us/a/img696/6874/mdlpworld22woj.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="320" src="http://imageshack.us/a/img696/6874/mdlpworld22woj.png" width="227" /></a></div>
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Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com0tag:blogger.com,1999:blog-7120134997435393696.post-43405929523033299262012-09-29T13:15:00.000-07:002012-09-29T14:25:19.958-07:00A quick update to SupportMix's Chromosome Painting<div dir="ltr" style="text-align: left;" trbidi="on">
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<span style="font-family: "Trebuchet MS",sans-serif;">A thoughtful reader of our blog has noticed that some of chromosome_paintings (Chr 5 set 9, Chr 7 sets 4,5; Chr 9 set 7, Chr 11 set 4) were missing in the original tar.gz bundle distributed via Google Data Drive. I've had to re-upload the archive (with missing files), the new location of the archive is <a href="https://docs.google.com/open?id=0B6n7iMc2P-yQOWtmNkxobzRCX2c">here</a>.</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><b>Additional experiment.</b></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">In addition to that quick fix, i decided to test the accuracy of SupportMix's chromosome paintings by juxtaposing them over the MDLP-World22 chromosome graphs. Due to time limitations, i used only first 7 chromosomes of my own SNP data. At first, i ran the MDLP-World22 modification of<a href="http://dodecad.blogspot.com/2011/09/do-it-yourself-dodecad-v-21.html"> DIYDodecad v2.1</a> in <i>byseg</i> mode on "windows" of 500 contiguous SNPs along a chromosome, slided by increments of 50. After that i cut out chromosome paintings of each chromosome from SupportMix's graphic output and aligned them to the scale of corresponding DIYDodecad chromosome graphs:</span></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi7855S0uQiAm5l8ip-IVl4UlyOtCaUT2BW2qG3Q-Hl-s5nVyGPivUOJCepr2qYyBGfhp-Cvj4yR_H_W6B7GtUQOyj4OvxuLe5n2keg6DLezYhhpzRdD9iD5Yrv9qr5ypwvBJLX9-U-ugw/s1600/chr2merged.gif" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="480" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi7855S0uQiAm5l8ip-IVl4UlyOtCaUT2BW2qG3Q-Hl-s5nVyGPivUOJCepr2qYyBGfhp-Cvj4yR_H_W6B7GtUQOyj4OvxuLe5n2keg6DLezYhhpzRdD9iD5Yrv9qr5ypwvBJLX9-U-ugw/s640/chr2merged.gif" width="640" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiN9mTpjaMRzJkmB6JcRmFM0MF_0Gu-mFm-mSUTFweNmSFf4u2YCH1U2h2QqKuBFpN7GlWs-H8z1m1DtSPk7f6kaVojCkFsNQ-u-NCabMr5pS7XPVSV81vjVlvjAJhaBr-xkgUJRbRL-_4/s1600/chr3merged.gif" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="480" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiN9mTpjaMRzJkmB6JcRmFM0MF_0Gu-mFm-mSUTFweNmSFf4u2YCH1U2h2QqKuBFpN7GlWs-H8z1m1DtSPk7f6kaVojCkFsNQ-u-NCabMr5pS7XPVSV81vjVlvjAJhaBr-xkgUJRbRL-_4/s640/chr3merged.gif" width="640" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEixRayaKciy_77jzBgG3XbrQFenLei3InsbVvXqh9ci7VgBeUfp9bt6QN21828lgIGLF7EKsOEdoXNuyiWCALFXck3DCMj-2-x8eYnm5yRRYc23MgWHKOnema5kqafYogSRu8YeuPuDSIs/s1600/chr4merged.gif" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="480" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEixRayaKciy_77jzBgG3XbrQFenLei3InsbVvXqh9ci7VgBeUfp9bt6QN21828lgIGLF7EKsOEdoXNuyiWCALFXck3DCMj-2-x8eYnm5yRRYc23MgWHKOnema5kqafYogSRu8YeuPuDSIs/s640/chr4merged.gif" width="640" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg3uUP9OAXCwIPd_tLJIYFEzSiEKsP3NMoQRAyWDlic7Y1ZZ1B49NOkXljTiJJZgKC8G997TNrnSFF9NGUWQ8aU_lBGWxo9Vo91VRXgAD_P7YwyUgbuzC2YGXpYi-xV-e4XNA8iEuj0rfc/s1600/chr5merged.gif" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="480" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg3uUP9OAXCwIPd_tLJIYFEzSiEKsP3NMoQRAyWDlic7Y1ZZ1B49NOkXljTiJJZgKC8G997TNrnSFF9NGUWQ8aU_lBGWxo9Vo91VRXgAD_P7YwyUgbuzC2YGXpYi-xV-e4XNA8iEuj0rfc/s640/chr5merged.gif" width="640" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEijxTLjXfwpXsBJeWx5Ng1k3-CL0zf1KCdUWLnqnOF3b9VkPhvtVfbhoj9hxTBqvtkH9FHdnnMnoQD3ksGrTJ8_tCfLXLVLX4abgEfFRXcySUQ3eZNvtFUE9Iv-Vwg3aFoxcODxCUTliWM/s1600/chr6merged.gif" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="480" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEijxTLjXfwpXsBJeWx5Ng1k3-CL0zf1KCdUWLnqnOF3b9VkPhvtVfbhoj9hxTBqvtkH9FHdnnMnoQD3ksGrTJ8_tCfLXLVLX4abgEfFRXcySUQ3eZNvtFUE9Iv-Vwg3aFoxcODxCUTliWM/s640/chr6merged.gif" width="640" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhuPGOADFYpi_86pBaNOo0BmcqZjtqcqPnu_Yecz-DQahNVmzst2y75HzlyO9bdvVo4i5Zpm8-AcrwfiSfTceBXSSd8YYdPtcUPDS97zDz3tKiLG-FahPknhvAW6jRMWR87G0FjtHQncIM/s1600/chr7merged.gif" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="480" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhuPGOADFYpi_86pBaNOo0BmcqZjtqcqPnu_Yecz-DQahNVmzst2y75HzlyO9bdvVo4i5Zpm8-AcrwfiSfTceBXSSd8YYdPtcUPDS97zDz3tKiLG-FahPknhvAW6jRMWR87G0FjtHQncIM/s640/chr7merged.gif" width="640" /></a></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"> After the preliminary evaluation of results, i have mentioned an approximate correlation between the <i>byseg</i>-output MDLP World22-DIYcalculator and SupportMix for two major "components" in my genome <b>(North-East-European and Atlantic-Mediterranean). Moreover, "Near-Eastern segments" (assigned by SupportMix" partially overlaps with the peaks of "Near-East segments" in DIYDodecad output.</b> However, the situation with the minor components is much less uncertain. The lack of correlation for the minor components could be explained by different factors:</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">1) DIYDodecad operates on the unphased raw data of genotypes</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">2) DIYDodecad program doesn't take into consideration genetic distance/recombination</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">3) last, but not least: small segments may appear more noisier than they are, because there
may not be any informative SNPs in a particular region to distinguish
between some of the minor ancestral components (Dienekes Pontikos' <a href="http://dodecad.blogspot.com/2011/08/few-comments-on-use-of-diydodecad-20.html">observation</a>)</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><b>UPDATE: At first i thought that it would be a great idea to calculate the index of correlation between 'byseg' output and SupporMix' Tprobs output file. But it seems that the results are not directly comparable - the assignment of segments in 'byseg' is measured in <i>frequencies</i>, while the assignment of segments in SupportMix is expressed by probability of assignment. If someone has a solution to this problem, please let me know.</b></span></div>
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Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com0tag:blogger.com,1999:blog-7120134997435393696.post-77478902873389632392012-09-28T16:22:00.001-07:002012-09-29T03:02:11.109-07:00Geography of Ancestry: the SPA analysis of the MDLP participants<div dir="ltr" style="text-align: left;" trbidi="on">
<span style="font-family: "Trebuchet MS",sans-serif;"><br /></span>
<span style="font-family: "Trebuchet MS",sans-serif;"><b>Geography of Ancestry: the SPA analysis of the MDLP participants</b></span><br />
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<span style="font-family: "Trebuchet MS",sans-serif;">A team of researchers (<a class="name" href="http://www.nature.com/ng/journal/v44/n6/full/ng.2285.html#auth-1"><span class="fn">Wen-Yun Yang</span></a><span class="comma">,</span><a class="name" href="http://www.nature.com/ng/journal/v44/n6/full/ng.2285.html#auth-2"><span class="fn"> John Novembre</span></a><span class="comma">,</span><a class="name" href="http://www.nature.com/ng/journal/v44/n6/full/ng.2285.html#auth-3"><span class="fn"> Eleazar Eskin</span></a><a class="name" href="http://www.nature.com/ng/journal/v44/n6/full/ng.2285.html#auth-4"><span class="fn">, Eran Halperin</span></a>) from Tel Aviv University (TAU) and University of
California, Los Angeles (UCLA) have created a method for more precisely
pinpointing the <a href="http://www.aftau.org/site/News2?page=NewsArticle&id=17086" target="_blank">geographic origin of a person's ancestry</a> by developing an understanding of the spatial diversity of genes. The analysis of diversity of genes within and between populations has
broad applications in studies of human disease and human migrations. The afore-mentioned team of researchers proposed
a new approach, spatial ancestry analysis, explicitly modeling the spatial distribution of each SNP
by assigning an allele frequency as a continuous function in geographic
space.<br /> </span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">Although the authors were more concerned with detecting the signals of selective sweeps in human genome, the SPA software implements some interesting features that could be immediately applied to the analysis of genetic data collected in open genome projects.</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">The most important one is that </span><span style="font-family: "Trebuchet MS",sans-serif;">the explicit modeling of the allele frequency allows individuals to be
localized on the map on the basis of <b>their genetic information alone.</b></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><b>From the original paper on <i>model-based approach for analysis of spatial structure in genetic data:</i></b></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><b>If the geographic origins of the individuals are known, one can use this
information to infer their allele frequency functions at each SNP.
However, if locations are not known, our model can infer geographic
origins for individuals using only their genetic data, in a manner
similar in spirit to PCA-based approaches for spatial assignment.</b></span></div>
</blockquote>
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<b> <span style="font-family: "Trebuchet MS",sans-serif;">The experiment</span></b><span style="font-family: "Trebuchet MS",sans-serif;"><br /></span><br />
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<span style="font-family: "Trebuchet MS",sans-serif;">Since the authors have made their software publicly available, I have decided to give <a href="http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CCAQFjAA&url=http%3A%2F%2Fgenetics.cs.ucla.edu%2Fspa%2F&ei=ExpmUKSEIY3R4QSk-IGgCw&usg=AFQjCNFxZIZcnN984ijGdHeclNoINFa46Q">SPA software </a>a try. A learning curve was very smooth, because three of five supported formats are in Plink format (with which i am familiar). Actually, the hardest part of experiment with SPA analysis was deciding what to do with the unknown geographic origins of the MDLP participants. Following the hint found in another interesting <a href="http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1002886">paper </a>(A Quantitative Comparison of the Similarity between Genes and Geography in Worldwide Human Populations), i divided the experiment into three parts:</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">1) first of all, i obtained the geographic coordinates (lats/longs) of each population included in the run. </span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">2) then i carried out SPA analysis with 3 specified dimensions</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">3) after the SPA analysis was finished, i applied Procrustes analysis
to compare the individual-level coordinates of the first two components
(1 and 2) in the SPA performed on the SNP data (1440447 snps) to the geographic
coordinates </span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">4) using Procrustes analysis, i identified an optimal alignment of the
genetic coordinates to the (Gilbert-projected) geographic
coordinates that involved a rotation of the longitudes and latitudes by 16<span class="inline-formula"><img src="http://www.plosgenetics.org/article/fetchObject.action?uri=info:doi/10.1371/journal.pgen.1002886.e012&representation=PNG" /></span> counterclockwise.</span></div>
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5) <span style="font-family: "Trebuchet MS",sans-serif;">finally, i projected the individual coordinates (which have been previously corrected for the optimal Procrustes alignment) onto the geographic map of Eurasia.</span></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjFn0TzVegrPmwVyucPoVXV_Il2qF-EyKB-535DesrCQC-SKeOavBVh59Fp87Nk1BSDfSPZhuU8qxD3EFxz4yHxijd50FZ6OIuunnyRrKepQ85ylGjJYpiN_EUpsAeeRSZL8cwnD53vxAc/s1600/MDLPmap.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="306" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjFn0TzVegrPmwVyucPoVXV_Il2qF-EyKB-535DesrCQC-SKeOavBVh59Fp87Nk1BSDfSPZhuU8qxD3EFxz4yHxijd50FZ6OIuunnyRrKepQ85ylGjJYpiN_EUpsAeeRSZL8cwnD53vxAc/s640/MDLPmap.png" width="640" /></a></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">The MDLP participants can find their final geographic coordinates in the corresponding <a href="https://docs.google.com/open?id=0B6n7iMc2P-yQeEZFaXpjM0Z1LWM">spreadsheet</a>. </span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><b>The allele frequency gradients and signals of recent positive selection</b></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">Another cool feature of SPA software is that it is able to identify loci showing extreme frequency gradients (i.e loci under selection), which does not
require grouping individuals into populations. These are
SNPs that show steep slopes of allele frequency change, with the
consideration that some of these might show extreme gradients because of
the impact of recent positive selection. </span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">The analysis of selective sweeps (as well as their possible implications) belongs to the domain of the molecular biology and medical genetics, and due to the project limitation i am not going to discuss them in all details. I'll limit my discussion by the following observations: the direction gradients of allele frequencies resembles the presupposed genetic flow from East Eurasia to West Eurasia, and from South-Europe to North-Europe. The first two dimensions of SPA </span><span class="st"><span style="font-family: "Trebuchet MS",sans-serif;">capture the main features of variation on the well-known </span><span class="st"><span style="font-family: "Trebuchet MS",sans-serif;">East-West Eurasian cline, while the second and third dimension represent the gene flow from South-Europe to North-Europe.</span></span></span></div>
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<span class="st"><span class="st"><span style="font-family: "Trebuchet MS",sans-serif;"> </span><br /><span style="font-family: "Trebuchet MS",sans-serif;"><br />I've sorted SNPs according to the value of slope function and it appears that the most extreme individual value is detected in <b>rs7568419</b> - a SNP, which is believed to have linked to a genetically inherited trait. Researchers at 23andMe have identified two genetic variants associated
with the trait in people of European ancestry. The C version of
rs10953183 is associated with more pronounced chin dimple and the C
version of <b>rs7568419</b> is associated with<b> less of a chin dimple</b>.</span></span></span></div>
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<span class="st"><span class="st"><span style="font-family: "Trebuchet MS",sans-serif;">A couple of factoids about a cleft chin from Wikipedia:</span></span></span><span class="st"><span class="st"></span></span></div>
<blockquote class="tr_bq">
<span style="font-family: "Trebuchet MS",sans-serif;">"This is an <a href="http://en.wikipedia.org/wiki/Mendelian_inheritance" title="Mendelian inheritance">inherited</a> trait in humans, where the <a href="http://en.wikipedia.org/wiki/Dominance_%28genetics%29" title="Dominance (genetics)">dominant</a> gene causes the cleft chin while the recessive <a href="http://en.wikipedia.org/wiki/Genotype" title="Genotype">genotype</a> presents without a cleft. However, it is also a classic example for variable <a href="http://en.wikipedia.org/wiki/Penetrance" title="Penetrance">penetrance</a><sup class="reference" id="cite_ref-4"><a href="http://en.wikipedia.org/wiki/Cleft_chin#cite_note-4">[5]</a></sup> with environmental factors or a <a class="mw-redirect" href="http://en.wikipedia.org/wiki/Modifier_gene" title="Modifier gene">modifier gene</a> possibly affecting the <a href="http://en.wikipedia.org/wiki/Phenotype" title="Phenotype">phenotypical</a>
expression of the actual genotype. Although cleft chins are seen
throughout the world, they are most predominate <b>among people of Germanic
and West Slavic (i.e., Polish) ethnicity. It is very common in that
part of the world and among descendants of people originating in that
part of Europe.<sup class="reference" id="cite_ref-5"><a href="http://en.wikipedia.org/wiki/Cleft_chin#cite_note-5">[6]</a></sup>It seems particularly prevalent among people living in the former Prussian areas of northern Poland bordering the Baltic Sea.</b>"</span></blockquote>
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<span style="font-family: "Trebuchet MS",sans-serif;">Those who are interested in more detailed analysis of loci under selection, could find SPA output file in <a href="https://docs.google.com/open?id=0B6n7iMc2P-yQS21KMVF1YmxCRDg">the corresponding spreadsheet</a> (note: a value of slope function in the last column). If you'll find an interesting SNP association with a particular trait, please report your finding to me.</span><br />
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<span style="font-family: "Trebuchet MS",sans-serif;"><b> </b> </span></div>
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Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com7tag:blogger.com,1999:blog-7120134997435393696.post-66905733768058245252012-09-23T08:08:00.003-07:002012-09-23T08:09:53.519-07:00Free SNP test offer from DNATribes<div dir="ltr" style="text-align: left;" trbidi="on">
I'm encouraging all MDLP participants who haven't had yet an opportunity to receive DNATribes Free SNP offer, send their Raw Data to Luke Martin for a free-of-charge analysis.<br />
<br />
<b>Free SNP Offer for Magnus Ducatus Lithuaniae Participants</b><br />
<br />
<blockquote>
"Good afternoon,<br />
<br />
We have followed with interest your Magnus Ducatus Lituaniae Project. In case you or any of your participants are interested, we would like to offer a free DNA Tribes SNP analysis for unrelated participants with four grandparents from the same country. (Grandparent birth places of U.S. and Canada are not included in this offer.) This would help us include less sampled populations in our geographical analysis.<br />
<br />
For free DNA Tribes SNP analysis, interested project participants can fill out the grandparent form (http://dnatribes.com/snpdiscount-project.html) and email their zipped genome file to snpsubmit@dnatribes.com between <b>now and October 1, 2012.</b><br />
<br />
If you have any questions, please let me know at dna@dnatribes.com.<br />
<br />
Best regards,<br />
Lucas Martin"</blockquote>
<br /></div>
Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com1tag:blogger.com,1999:blog-7120134997435393696.post-45841702906972121472012-09-20T10:19:00.001-07:002012-09-20T10:20:19.498-07:00The component maps of MDLP-World22 calculator<div dir="ltr" style="text-align: left;" trbidi="on">
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I would like to express my gratitude to the fellow members of ABF - <b>Loxias and Wojewoda</b>- for creating amazing maps of components and plots showing interrelationships between 22 components.</div>
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Since the readers of my blog might be interested in visual inspecting of components , i have decided to upload them on-line. </div>
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The first batch of maps includes "the component portraits", created by Loxias:</div>
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<table cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: 0px; margin-right: 0px; text-align: left;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjlK0qjDcLpE3kOot-doPaER1KA2HzDKq0hqlBzagtj0bKyZia8BUrQyXRyqd8ocZVSAsEDtgRwD-cMH5iuP6FnAHCVrul07XLZpzGhfsTQOkN3dj325Ul9FtzsQgK6ynkthyCYdQOrBjw/s1600/MDLPwestasian.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="245" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjlK0qjDcLpE3kOot-doPaER1KA2HzDKq0hqlBzagtj0bKyZia8BUrQyXRyqd8ocZVSAsEDtgRwD-cMH5iuP6FnAHCVrul07XLZpzGhfsTQOkN3dj325Ul9FtzsQgK6ynkthyCYdQOrBjw/s320/MDLPwestasian.jpg" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">West-Asian</td></tr>
</tbody></table>
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<table cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: 0px; margin-right: 0px; text-align: left;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgbA4DpRKyhfwZpwjevvdKfpOv8wSdamvgioTZZ8APW-3tWMNo2o8i-aSUI5fUfWdgcC5YXNpgEuMrHjqCpJeL166-fubfcYs8mgSU21yPeJwgkTBZ7iYMsgEkIctVWPrcPjkvDVCs0wIM/s1600/MDLPatlantomed.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="245" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgbA4DpRKyhfwZpwjevvdKfpOv8wSdamvgioTZZ8APW-3tWMNo2o8i-aSUI5fUfWdgcC5YXNpgEuMrHjqCpJeL166-fubfcYs8mgSU21yPeJwgkTBZ7iYMsgEkIctVWPrcPjkvDVCs0wIM/s320/MDLPatlantomed.jpg" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Atlantic-Mediterranean</td></tr>
</tbody></table>
<table cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: 0px; margin-right: 0px; text-align: left;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEikVRtV_cOHXjHXx-DWM0OnoDw42mMuXTL7-z6iS_402du4gsBqWBXgk95Hz7eILZpWA59tiKqnnYBw30cGRO3X8SfmZfzpiMKo6YxAQweMJE_rFsFzd6jZ6dHGK5Ii6sPZ1dQtIoK5bwo/s1600/MDLPeastsiberian.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="245" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEikVRtV_cOHXjHXx-DWM0OnoDw42mMuXTL7-z6iS_402du4gsBqWBXgk95Hz7eILZpWA59tiKqnnYBw30cGRO3X8SfmZfzpiMKo6YxAQweMJE_rFsFzd6jZ6dHGK5Ii6sPZ1dQtIoK5bwo/s320/MDLPeastsiberian.jpg" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">East-Siberian</td></tr>
</tbody></table>
<table cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: 0px; margin-right: 0px; text-align: left;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgova79DVESJQoqBT7vS8doC1ZQ4ct5shhkGCMi4XdswY4lXXS866YA89X6i9YLI_jnm8GyhprmVDcRLU_c13FcKFFtFvmUtq8-q1i_c0k13CykOf1RxBTpnavQvJx2sLREkeQpK_x_vrI/s1600/MDLPamerind.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="245" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgova79DVESJQoqBT7vS8doC1ZQ4ct5shhkGCMi4XdswY4lXXS866YA89X6i9YLI_jnm8GyhprmVDcRLU_c13FcKFFtFvmUtq8-q1i_c0k13CykOf1RxBTpnavQvJx2sLREkeQpK_x_vrI/s320/MDLPamerind.jpg" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Amerind</td><td class="tr-caption" style="text-align: center;"></td></tr>
</tbody></table>
<table cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: 0px; margin-right: 0px; text-align: left;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg5CRekuA2k1S_FjD9_4exGWuwRgfO4SkikIOnq3ft6c0G8Yxug97Z1IZ4ifc3GI84Sa0dNOWz0vjEytzKAomoJq9m9DyPfZv0nSTnHqsIM_X1Wtv2RBRFuLJS-PaHiZXR_LEu39oH5kRQ/s1600/MDLPindian.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="245" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg5CRekuA2k1S_FjD9_4exGWuwRgfO4SkikIOnq3ft6c0G8Yxug97Z1IZ4ifc3GI84Sa0dNOWz0vjEytzKAomoJq9m9DyPfZv0nSTnHqsIM_X1Wtv2RBRFuLJS-PaHiZXR_LEu39oH5kRQ/s320/MDLPindian.jpg" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Indian</td></tr>
</tbody></table>
<table cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: 0px; margin-right: 0px; text-align: left;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiL4gTFYhi-XE7ZdQ87SHzSajU5va9xw5qucn2tAyc3kttWK2alni82gtSDPvcPaG3B0xb079ydM4bSvN2qsT8DB9BjorWEp7uAGnX5Sk7E5FqUnForgQn35tq-RKLhcu3ymjnPjv614ew/s1600/MDLPindoiranian.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="245" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiL4gTFYhi-XE7ZdQ87SHzSajU5va9xw5qucn2tAyc3kttWK2alni82gtSDPvcPaG3B0xb079ydM4bSvN2qsT8DB9BjorWEp7uAGnX5Sk7E5FqUnForgQn35tq-RKLhcu3ymjnPjv614ew/s320/MDLPindoiranian.jpg" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Indo-Iranian</td></tr>
</tbody></table>
<table cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: 0px; margin-right: 0px; text-align: left;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg0biF7ofdqcdE6WtGQFexTchtYHCQYJHQx6A0iN5Ymv8JKj-8wPnuvvZ7bj1vKtU5JEa-GeYj8RWa9h2-G4GfCJsnXwGyLqRdtDSUmsCSS6cznF2XuO4I-lT9Lo2YUpiQ5B60K4IadnGk/s1600/MDLPindotibetan.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="245" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg0biF7ofdqcdE6WtGQFexTchtYHCQYJHQx6A0iN5Ymv8JKj-8wPnuvvZ7bj1vKtU5JEa-GeYj8RWa9h2-G4GfCJsnXwGyLqRdtDSUmsCSS6cznF2XuO4I-lT9Lo2YUpiQ5B60K4IadnGk/s320/MDLPindotibetan.jpg" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Indo-Tibetan</td></tr>
</tbody></table>
<table cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: 0px; margin-right: 0px; text-align: left;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjHdZwo9M8R-Qyhy82rVO6vqIZu7GikmL5wXpA3IxSD89lm69iXtfDuCvaq6wb1s-1nIgRWXvLGuHdkjFe7u-2TgPQ7TIWE1v_Qqd2bpz8dLuCdH04ieYQJoqb_0bTEDPbjM7tW4eNVYxo/s1600/MDLPpaleosiberian.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="245" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjHdZwo9M8R-Qyhy82rVO6vqIZu7GikmL5wXpA3IxSD89lm69iXtfDuCvaq6wb1s-1nIgRWXvLGuHdkjFe7u-2TgPQ7TIWE1v_Qqd2bpz8dLuCdH04ieYQJoqb_0bTEDPbjM7tW4eNVYxo/s320/MDLPpaleosiberian.jpg" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Paleo-Siberian</td></tr>
</tbody></table>
<table cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: 0px; margin-right: 0px; text-align: left;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjt5kfFV99q_wRYXTmVMU7UUU_uIm5KnJxEpPsz6WolayL_G3_hqpf1iSI2Ut0WSwit1_CK-oE6kmWOf54G5XB5BV1ppLUVGg7mlTeyuO2tFSnSpEsfZx-IAOS4p5BjJXeWz8y2q2ZzHGo/s1600/MDLPpygmy.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="245" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjt5kfFV99q_wRYXTmVMU7UUU_uIm5KnJxEpPsz6WolayL_G3_hqpf1iSI2Ut0WSwit1_CK-oE6kmWOf54G5XB5BV1ppLUVGg7mlTeyuO2tFSnSpEsfZx-IAOS4p5BjJXeWz8y2q2ZzHGo/s320/MDLPpygmy.jpg" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Pygmy</td></tr>
</tbody></table>
<table cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: 0px; margin-right: 0px; text-align: left;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhLQ0UdbkHW8bOCcW6d_FA3EmKD_LXh-eHxBDgAai2rqrlqbXWBdPTHm2r5DFKLdeyD3c_n_o0SNuOGJs8E74b4uRLMH5nZE0XBgQUZfibWzxz36RRFdKA3GD6r6RzQ38-_TH6kA4wvZw0/s1600/MDLPsubsaharan.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="245" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhLQ0UdbkHW8bOCcW6d_FA3EmKD_LXh-eHxBDgAai2rqrlqbXWBdPTHm2r5DFKLdeyD3c_n_o0SNuOGJs8E74b4uRLMH5nZE0XBgQUZfibWzxz36RRFdKA3GD6r6RzQ38-_TH6kA4wvZw0/s320/MDLPsubsaharan.jpg" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Sub-Saharan</td><td class="tr-caption" style="text-align: center;"></td></tr>
</tbody></table>
<table cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: 0px; margin-right: 0px; text-align: left;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgv3MoAJvI6Xyaleb4fzL_7yKp5FlusLp83YpYR8lGAIcFObHS-eLeCTZxKxxr2zM-ygW52cRDqgLWwzXog1a08iGFiiMBYW1O8_Ge38BTz7avDtd1a-k7qfJOtPmMvCdQ2M-JwcZj948k/s1600/MDLPneareast.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="245" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgv3MoAJvI6Xyaleb4fzL_7yKp5FlusLp83YpYR8lGAIcFObHS-eLeCTZxKxxr2zM-ygW52cRDqgLWwzXog1a08iGFiiMBYW1O8_Ge38BTz7avDtd1a-k7qfJOtPmMvCdQ2M-JwcZj948k/s320/MDLPneareast.jpg" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Near-East</td><td class="tr-caption" style="text-align: center;"></td></tr>
</tbody></table>
<table cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: 0px; margin-right: 0px; text-align: left;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEic9q87HGmlqcuAOeiaX3IBaF6JMOlR3y7qF0clgaTUUqMc8Cy3KH4MR0CO8uYg24awnqRgGpISWTki4EMRhhXUdRaKkWdfGf_m0pkPbkbnxk2P1ZsjTvRIaN18uGSxCY-5tscYvN-AxGE/s1600/MDLPnortheasteuro.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="245" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEic9q87HGmlqcuAOeiaX3IBaF6JMOlR3y7qF0clgaTUUqMc8Cy3KH4MR0CO8uYg24awnqRgGpISWTki4EMRhhXUdRaKkWdfGf_m0pkPbkbnxk2P1ZsjTvRIaN18uGSxCY-5tscYvN-AxGE/s320/MDLPnortheasteuro.jpg" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">North-East-European</td></tr>
</tbody></table>
<table cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: 0px; margin-right: 0px; text-align: left;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhNJiTkhMpw7BjEIKdOMYwt57NIPQ5QdvyeWMhDqv9AVI8uIsJWvW5h-XVAvrDessSKCKLi6HdnwJ3gLZKRoWlGkx9Wu00kthYlrC6npNzd08zf-TMVCMm6D1hyphenhyphen5EUcdMCqBgnIeb9e8ow/s1600/MDLPnorthsiberian.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="245" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhNJiTkhMpw7BjEIKdOMYwt57NIPQ5QdvyeWMhDqv9AVI8uIsJWvW5h-XVAvrDessSKCKLi6HdnwJ3gLZKRoWlGkx9Wu00kthYlrC6npNzd08zf-TMVCMm6D1hyphenhyphen5EUcdMCqBgnIeb9e8ow/s320/MDLPnorthsiberian.jpg" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">North-Siberian</td></tr>
</tbody></table>
<table cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: 0px; margin-right: 0px; text-align: left;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgO-sG4zfCFKtQ3jdgCxH1Rsdr0QjG3LGY_j31wTr5t4K8CxPOL5_GJup0nTGnWfJUtwECBKc730inJzqFA0kpu3mHlr1_Pw4MGjDje_OYQEcB20Hf4MgIQUN-oVBSn134FdOOK5-SK1Gg/s1600/mdlpmesolithic.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="254" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgO-sG4zfCFKtQ3jdgCxH1Rsdr0QjG3LGY_j31wTr5t4K8CxPOL5_GJup0nTGnWfJUtwECBKc730inJzqFA0kpu3mHlr1_Pw4MGjDje_OYQEcB20Hf4MgIQUN-oVBSn134FdOOK5-SK1Gg/s320/mdlpmesolithic.jpg" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">North-Mesolithic-European</td></tr>
</tbody></table>
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The second batch includes <span id="sp0015">the PCA scatter plot of components</span>, created by Wojewoda.<span id="sp0015"> PCA
scatter plots one PCA component vs. another PCA component of data obtained from ancestry coefficients collected for each of MDLP World22 components: <b>the spots are
connected over time to produce a trajectory for each component.</b></span></div>
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Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com5tag:blogger.com,1999:blog-7120134997435393696.post-85368604288424591382012-09-19T16:29:00.002-07:002012-09-19T16:37:45.825-07:00Paint Me a Rainbow: Painting World 22 ancestral components<div dir="ltr" style="text-align: left;" trbidi="on">
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<span style="font-family: "Trebuchet MS",sans-serif;">This update will be concerned with inter-related concepts of "chromosome painting" and admixture. Modern genetics and personal genomics, particularly in the last 2-5 years, had paid very considerable attention to them, sometimes under the rubric of " determining ancestral origin of genomic segments".</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">In 2011 year, i performed a couple of experiments with <a href="http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CB0QFjAA&url=http%3A%2F%2Flamp.icsi.berkeley.edu%2F&ei=FzpaUJTtKonk4QSbzIHwCw&usg=AFQjCNF5KkvJKXYYPlj8cOpJvuoMbjfRGg">LAMP software</a> (cf. <a href="http://magnusducatus.blogspot.com/2011/05/experimental-test-iii-deconstructing.html">Experimental test III: (De)constructing ancestry with LAMP</a> and <a href="http://magnusducatus.blogspot.com/2011/12/experimental-test-running-admixture-on.html">Experimental test: estimating ancestries at each locus in a population of admixed individuals (LAMP))</a>).</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">Although the experiments met <span class="st"><i></i>with moderate success, i wasn't satisfied with the results and decided to postpone the forthcoming experiments with chromosome painting to a future day. In so doing, i endorsed increasing appreciation of the distinction between population stratification's algorithms, implemented in LAMP and <a href="http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CCUQFjAA&url=http%3A%2F%2Fwww.genetics.ucla.edu%2Fsoftware%2Fadmixture%2F&ei=3zpaUIHkH6Oh4gTu04CADw&usg=AFQjCNF9ntG3p4aideTtrTOgydsJsf1yPQ">ADMIXTURE</a>.<br /><br />I have already discussed the differences between LAMP and Admixture, but in illustrating the idea of experiment, i need to turn to my previous explanation again:</span> </span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">1) ADMIXTURE software
implements a model-based approach to estimate ancestry coefficients as
the parameters of a statistical model. It is also important to add that
the model-based approach in ADMIXTURE is based on the global ancestry
paradigm <b>(i.e the goal of ADMIXTURE/STRUCTURE analysis is to
estimate the proportion of ancestry from each contributing population,
considered as an average over the individual's entire
genome).</b></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">2) LAMP software is built upon
an efficient dynamic-programming algorithm WINPOP that infers
locus-specific ancestries.Genome is partitioned into chromosome segments
of definite ancestral origin (overlapping, contiguous windows of SNPs)
and likelihood model optimized over each window. T<b>he goal then is to find the segment boundaries and assign each segment's origin.</b></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><b>I understand the problem in terms of the ancestry assignment. My experience shows that methods based on the inference of locus-specific ancestries are usually very accurate for ancestral deconvolution of genotype data that has consistently been shown to do better than more popular statistical and PCA-based methods, while being able: <br />1) to handle more than two ancestral populations<br />2) to model the paths of recombination between ancestral segments.</b>In June 2012, Jason Mezey Lab (Cornell University) released <a href="http://mezeylab.cb.bscb.cornell.edu/Software.aspx">SupportMix</a> - a machine learning algorithm for determining ancestral origin of genomic segments
when analyzing individuals from a population with a recent or ancient history of admixture. As regards the accuracy of the software, the authors argued that SupportMix provides a robust tool for accurate and robust ancestral assignment by simultaneous analysis of a worldwide selection of ancestral populations. Such analyses will be critical for accurate assignment in the many world-wide admixed populations that are likely to have unexpected ancestry that reflects a richer history than known from anthropological or historical studies (from the provisional paper: <a href="http://www.biomedcentral.com/1471-2156/13/49/abstract">Omberg et al.2012 "Inferring genome-wide patterns of admixture in Qataris using fifty-five ancestral populations"</a>). The cited paper includes a number of other claims important for any analysis of genetic admixture: the accuracy of ancestry assignment was lower for more closely related populations but better than LAMP-ANC, a method that was been shown to consistently outperform other ancestry deconvolution methods.<br /><br />This overly optimistic conclusion influenced my choice between LAMP-ANC and SupportMix in favor of latter. To be honest, i'm not the first genome blogger to use Supportmix - in July of 2012 Polako from Eurogenes carried out<a href="http://bga101.blogspot.com/2012/07/looking-beyond-finnish-genetic.html"> a loci-specific analysis of Finnish genomes using SupprotMix.</a> I decided to repeat this experiment. There is, of course, a significant difference between Polako's analaysis and my experiment. While Polako was using the modern populations as 'putative' donor populations, the final goal of my design was to imitate the results of <a href="http://www.yourgeneticgenealogist.com/2012/06/23andme-announces-beta-testing-of-new.html">the long-awaited update of 23andme's Ancestry Painting</a>, which is is being updated to offer more detailed results based on approximately
20 world regions, drawn from both customer data and academic reference
populations. In order to do so, i have used the dummy set of 22 simulated putative ancestral populations simulated from<a href="http://magnusducatus.blogspot.com/2012/09/behind-curtains-mdlp-world-22-showcase.html"> the allele frequencies of the World-22 calculator.</a><br /><br /><b>The experiment</b></span><br />
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<span style="font-family: "Trebuchet MS",sans-serif;">SupportMix requires at least three input files. One file for each of the putative ancestral populations and one file containing the genetic information of the admixed individuals with additional requirement that he markers have to be phased. Each population should be represented by two files in <a href="http://pngu.mgh.harvard.edu/%20purcell/plink/data.shtml#tr">Plink transposed format</a>, a .tped file and a .tfam file. <br /><br />The markers (80751 SNPs) were phased per each chromosome using default settings in <a href="http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&cad=rja&ved=0CC8QFjAB&url=http%3A%2F%2Ffaculty.washington.edu%2Fbrowning%2Fbeagle%2Fbeagle.html&ei=9UpaUNeEO8r_4QTqrIDAAQ&usg=AFQjCNEEioOamCBusEPI9Ifzw_TfSzn20g">BEAGLE</a> software. While the original Plink format does not specify the order of the alleles in in the file, SupportMix works with phased data. Keeping that in mind, i have converted BEAGLE-phased dataset directly into Plink's tped format without pre-processing the dataset in Plink (hint: <a href="http://www.pypedia.com/index.php/Convert_beagle_to_TPED_user_Kantale">Kantele's beagle_to_tped script</a>). Then i used UNIX text processing utilities to extract the genotypes from ancestral populations into the corresponding subsets ('references') and split the project dataset (93 individuals) into 9 subgroups.<br /><br />Finally, i have interpolated the genetic map position of each SNP along chromosome using <a href="http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CCMQFjAA&url=http%3A%2F%2Fcompgen.rutgers.edu%2Fmaps&ei=q0xaUJyBCJGL4gS1mICQCw&usg=AFQjCNErbyGD4_AvPVwUe7OxyfJ0XrbhCQ">Rutgers genetic maps.</a></span><br />
<span style="font-family: "Trebuchet MS",sans-serif;"> SupportMix was run by specifying a configuration file with the default options: (window_size =400, generations_from_admixture_event=6).</span><br />
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<span style="font-family: "Trebuchet MS",sans-serif;">Below are some screenshots of SupportMiX output for the MDLP project participants:</span><br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgevWyX0GQhGoUzfCvppKzZQLglEVuL9Yy1lurNeMGwiRgqLXvi4bzwU_dJmtb2ruoO6gNQC-r__9f0zcyDfnqzZ_o32D4fKFpz3JL0i2SHKF_-PNwTe874eEYi78qii5kn5eB50n7onBk/s1600/chr1set2.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="240" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgevWyX0GQhGoUzfCvppKzZQLglEVuL9Yy1lurNeMGwiRgqLXvi4bzwU_dJmtb2ruoO6gNQC-r__9f0zcyDfnqzZ_o32D4fKFpz3JL0i2SHKF_-PNwTe874eEYi78qii5kn5eB50n7onBk/s320/chr1set2.png" width="320" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhMWeulvh9E4vwzP4b-gKOSMvyUYKGcYiokNCLDDa8aQooJboP_Vj0rSTuDrcQIlBbzBb3pzSJXzIwghr8I_VRD7WNsCa1ExaF0B8UasC0ZUEgce39MDuqEECcQ8_wIvsZtfFw_TjkMr_Y/s1600/chr2set4.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="240" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhMWeulvh9E4vwzP4b-gKOSMvyUYKGcYiokNCLDDa8aQooJboP_Vj0rSTuDrcQIlBbzBb3pzSJXzIwghr8I_VRD7WNsCa1ExaF0B8UasC0ZUEgce39MDuqEECcQ8_wIvsZtfFw_TjkMr_Y/s320/chr2set4.png" width="320" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhqKUjvoRMXwnBhwkCJmVmMvoU5F9gdWWUDri6DTDh1wS7HTR3Uk4VWynVT0eJSbksJkIveEkwimKfjSTIr-7kVuUtcLym4x-dTPNWG60gvA7N-HTEsbEhVQvZreYkLaQFnmxU318nM1h4/s1600/chr19set9.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="240" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhqKUjvoRMXwnBhwkCJmVmMvoU5F9gdWWUDri6DTDh1wS7HTR3Uk4VWynVT0eJSbksJkIveEkwimKfjSTIr-7kVuUtcLym4x-dTPNWG60gvA7N-HTEsbEhVQvZreYkLaQFnmxU318nM1h4/s320/chr19set9.png" width="320" /></a></div>
<span style="font-family: "Trebuchet MS",sans-serif;"><br />Please note that each 'recipient' (i.e the project participant) is represented by two <b>phased </b>chromosomes, i.e V199_<b>a </b>and V199<b>_b. </b>The color legend of the components used in the analysis, has been attached to the right side of the plot.<br /><br /><b>The complete set (Chr.1-22 for all project participants) in tar.gz format (14.6 Mb) could be <a href="https://docs.google.com/open?id=0B6n7iMc2P-yQQkVhQ2ttQVlUTWs">downloaded here</a>. </b><br /><br /><b><br />SupportMix results: what to do next.</b></span><br />
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<span style="font-family: "Trebuchet MS",sans-serif;">First of all, i encourage every participant of my project to compare their results to "chromosome painting" in MDLP World-22 calculator on John Olson's <a href="http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CB4QFjAA&url=http%3A%2F%2Fgedmatch.com%2F&ei=elJaUN-eKYbh4QTh54BI&usg=AFQjCNF-hbkoNPdt65bC3N27Go7CIG_zIQ">Gedmatch </a>site. I have to contemplate the possibility that the painting on Gedmatch site might be different from that one produced by SupportMix. I would also suggest to compare SupportMix's paintings to other calculators' paintings and 23andme's Ancestry Finder, etc.</span><br />
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<span style="font-family: "Trebuchet MS",sans-serif;">If you are familiar with basic techniques of image editing software, then it is a good idea to have your chromosomes cut&merged into the composite image (see example below):<br /><br /><br /> <br /> </span><br />
<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj0_4XVFLpk1w8voodLTQcrI666RCdRijV26D1K6YPVRcjsgNP3IbjooZ9uxz6mGLwWd0VHbtPb7QD2F-0_RjwuqD9qfLTRzb2t3F9TZPEdIYBBgiIaUvdKWCBsEAzLej-HUPHimrR_jms/s1600/combined-painting.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="400" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj0_4XVFLpk1w8voodLTQcrI666RCdRijV26D1K6YPVRcjsgNP3IbjooZ9uxz6mGLwWd0VHbtPb7QD2F-0_RjwuqD9qfLTRzb2t3F9TZPEdIYBBgiIaUvdKWCBsEAzLej-HUPHimrR_jms/s400/combined-painting.png" width="262" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;"><b>Chromosome Painting (in 23andme's style)</b></td><td class="tr-caption" style="text-align: center;"><br /></td><td class="tr-caption" style="text-align: center;"><br /></td><td class="tr-caption" style="text-align: center;"><br /></td></tr>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjBovrq3TBnoswmQdgUyLbwBZTyXASzd6vlkSgQR-SPtLV-n2w52MSVS-RPTOrBW0Kl8S8W2i-qaI7Av5w-j1-IiXnuZLUcc_Mde02m8UVyzWfyQvLTOEOe7EvsT8JRUzkkrAcxku9fF34/s1600/AF-combined-painting.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="262" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjBovrq3TBnoswmQdgUyLbwBZTyXASzd6vlkSgQR-SPtLV-n2w52MSVS-RPTOrBW0Kl8S8W2i-qaI7Av5w-j1-IiXnuZLUcc_Mde02m8UVyzWfyQvLTOEOe7EvsT8JRUzkkrAcxku9fF34/s400/AF-combined-painting.png" width="400" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;"><b>Chromosome Painting (an imitation of 23andme's Ancestry Finder)</b></td></tr>
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<span style="font-family: "Trebuchet MS",sans-serif;"> <br /><br /><b><br /> </b></span><br />
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Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com0tag:blogger.com,1999:blog-7120134997435393696.post-20377735452300035282012-09-15T13:20:00.000-07:002012-09-15T13:20:32.020-07:00The reliability of 'ancestral components' in MDLP World-22 calculator: trying TreeMix on 22 ancestral components<div dir="ltr" style="text-align: left;" trbidi="on">
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<span style="font-family: "Trebuchet MS",sans-serif;">In the <a href="http://arxiv.org/abs/1206.2332">recent paper</a> of Pickrell and Pritchard outlined the most challenging problems in the analysis of relationships between populations: </span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><i>Many aspects of historical relationships between populations are
reflected in genetic data. Inferring these relationships from dense
genetic data remains a challenging and very difficult task. </i></span></blockquote>
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<span style="font-family: "Trebuchet MS",sans-serif;"><br />One such aspect is the (re)construction of ancestral population from precomputed
allele frequencies.In the recent supervised Admixture analysis of the
MDLP analysis (see <a href="http://magnusducatus.blogspot.com/2012/09/behind-curtains-mdlp-world-22-showcase.html">previous post</a>), i have carried the analysis of
dataset which consists of both extant populations and 'simulated un-admixed
populations'. However, one can always question the accuracy of the
results of such an experiment by posing a very simple question: is it
possible to carry out the simultaneous analysis of 22 putative
ancestral populations <b>while being independent of prior demographic
information ( involving population splits, gene flow, and changes in population size). Accounting for demographic information is especially important in cases when we have only limited genetic data for the few
ancestral populations that are known with greater certainty.</b> </span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">To the ultimate relief of genome bloggers, Joe Pickrell and Jonathan Pritchard
<a href="http://precedings.nature.com/documents/6956/version/1/files/npre20126956-1.pdf"> have released</a> a companion program to Structure/Admixture programs called TreeMix. TreeMix uses large SNP data sets to estimate the relationships among populations
including both population splits and admixture events.
According to Pickrell and Pritchard, the new method provides a better representation of population histories than do standard tree-building methods when they
are applied to the worldwide populations. In my opinion, the real advantage of TreeMix over traditional admixture programs is that it accounts for unknown ancestral allele frequencies. Indeed, in most cases we do not know the ancestral values of allele frequencies, but instead only the values in sampled descendant populations.</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">I decided to give TreeMix a try on 22 putative ancestral ADMIXTURE components from the latest run. For this purpose, <a href="http://dienekes.blogspot.com/2012/03/auxiliary-treemix-scripts.html">I used a conversion script, which was kindly provided by Dienekes Pontikos.</a> This script takes ADMIXTURE P file and converts it into a plink.treemix.gz file, which is ready for input into TreeMix.</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"> I ran TreeMix using following settings > <span style="font-size: x-small;">treemix -i MDLPworld22.treemix.gz -root South-African -k 500 -o MDLP22world</span> (consult <a href="http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CCAQFjAA&url=http%3A%2F%2Ftreemix.googlecode.com%2Ffiles%2Ftreemix_manual.pdf&ei=SM5UUJGbE8XQ4QTsvIDgCg&usg=AFQjCNFuN6Fn43cmVaUagTrarAmJM_exfg">TreeMix manual </a>for explanation of program parameters). </span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhwgt-6wIrH1ICazRy_B-KK8HuajpA7sxw7TvQkLVQ34K5XpRzUW223nuqLod-c_BmnaHWX_3kyfGQrtdAq_ERiUSpmfO1t6vVqN-5u4Nw3ECadNurKIzrC6RA1apfjkvGNVZlyCEsTc7c/s1600/MDLD22world.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="340" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhwgt-6wIrH1ICazRy_B-KK8HuajpA7sxw7TvQkLVQ34K5XpRzUW223nuqLod-c_BmnaHWX_3kyfGQrtdAq_ERiUSpmfO1t6vVqN-5u4Nw3ECadNurKIzrC6RA1apfjkvGNVZlyCEsTc7c/s400/MDLD22world.png" width="400" /></a></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><br /><br />After careful examination of the output tree, i was really surprised by how remarkably similar the tree is to that one in the original paper of Pickrell & Pritchard:</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEic6gOy0o0FVP0c8-LHUhkMDVQJe2gQlSARXXR2XbFnVmpU9K6n0K8AbMeUaZpLDyPv85eh8L-bPbj-zgq8sloWi0SAoR70eDKtA43GHx1scFTeUe3EghWQYaGlYaauoi-R7dpt2iBymGQ/s1600/pritchard.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="316" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEic6gOy0o0FVP0c8-LHUhkMDVQJe2gQlSARXXR2XbFnVmpU9K6n0K8AbMeUaZpLDyPv85eh8L-bPbj-zgq8sloWi0SAoR70eDKtA43GHx1scFTeUe3EghWQYaGlYaauoi-R7dpt2iBymGQ/s320/pritchard.png" width="320" /></a></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><br /><br /><br /><br /><br />In the next of experiment i have introduced to the tree a rudimentary model of migrations/gene flows by including -m 5 parameter. The model is, however, very rudimentary, because Pritchard and Pickrell have modeled "migration between populations as occurring at single, instantaneous time points. This is, of course, a dramatic simplification of the migration process. This model will work best when gene flow between populations is restricted to a relatively short time period. Situations of continuous migration violate this assumption and lead to unclear results" (see the cited paper for the further discussion).</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjntzjrWna7wh4IXq4Nh_M-L5iP4v2Qiw_3KCk-Ql5V4kBg8sdoCWoB3ub3LQgX52JGTkkg_RwXAoK9q6AL0L8JyCJ2A6C2s784yhu9w_OtO9FuwiZkJlKWHco2RvhrkMa0Hy_DCrdHVyg/s1600/MDLD22world-migs.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="272" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjntzjrWna7wh4IXq4Nh_M-L5iP4v2Qiw_3KCk-Ql5V4kBg8sdoCWoB3ub3LQgX52JGTkkg_RwXAoK9q6AL0L8JyCJ2A6C2s784yhu9w_OtO9FuwiZkJlKWHco2RvhrkMa0Hy_DCrdHVyg/s320/MDLD22world-migs.png" width="320" /></a></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"> Nevertheless, we may, <span class="st"> though <i>with all due caution</i>, speculate about the hypothetical gene flow directions:<br /><br /><b>a) from East-South-Asian ancestral component -> to Tibetan ancestral component</b></span></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><b><span class="st">b) from the split_point between Austronesian and Melanesian ancestral components -> to <span class="st">East-South-Asian ancestral component</span></span></b></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><b><span class="st"><span class="st">c) from the split_point between East-Siberian and East-South-Asian -> to the split_point between Indian and ((Austronesian;Melanesian) Tibetian)* ancestral component</span></span></b></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><b><span class="st"><span class="st">d) and finally, from North-European-Mesolithic component to the split_point between West-Asian and (North-East-European; Atlantic-Mediterranean-Neolithic)* component.</span></span></b></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><b><span class="st"><span class="st">The last point d) calls for a further explanation. As one can see from the attached population tree,North-European-Mesolithic component is unexpectedly shifted towards East-Asian populations. Despite of all simplicity of test, i think that the result in consideration could probably support a recent statement made by David Reich in the recent <b><a href="http://dienekes.blogspot.com/2012/07/reconstructing-origin-of-native.html">Reich et al. (2012)</a></b> paper:</span></span></b><b><span class="st"><span class="st"></span></span></b></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><b> </b><i>we took advantage of the fact that east/central Asian admixture has
affected northern Europeans to a greater extent than Sardinians (in our
separate manuscript in submission, we show that this is a result of
the different amounts of central/east Asian-related gene flow into
these groups).</i></span></blockquote>
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<span style="font-family: "Trebuchet MS",sans-serif;"><span class="st"><span class="st">Cf. also Dienekes' <a href="http://dienekes.blogspot.com/2012/07/hints-of-eastcentral-asian-admixture-in.html">comments</a> </span></span></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><span class="st"><span class="st">If our finding is congruent Reich's hypothesis, then one could assume that </span></span><span class="st"><span class="st"><span style="background-color: white;">he Mesolithic Europeans were Asian-shifted </span><a href="http://dienekes.blogspot.com/2012/06/mesolithic-iberians-la-brana-arintero.html" style="background-color: white;">themselves</a><span style="background-color: white;">, i.e the earliest episode of admixture could have occurred in the Mesolithic period.</span> </span></span></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><span class="st"><span class="st"><u><b>UPDATE: </b></u></span></span></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><span class="st"><span class="st">The same scenario seems to be supported in </span></span><a href="http://dienekes.blogspot.com/2012/09/estimating-admixture-proportions-and.html">(Patterson et al. 2012).</a></span></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiI8k6LeyJqJVew234ShQ3yibDeC980boxjYeWxzydy1n2TFcKVrA3wX2Z44vlpDxKKefq0BKF5nZT5NorM0YOPvwWOb_bcifJVocQgmz9A_7Ti-Zl_-K5jvRPPvYcd9zeHxhDSKYZ0aF0/s640/figure9.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="140" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiI8k6LeyJqJVew234ShQ3yibDeC980boxjYeWxzydy1n2TFcKVrA3wX2Z44vlpDxKKefq0BKF5nZT5NorM0YOPvwWOb_bcifJVocQgmz9A_7Ti-Zl_-K5jvRPPvYcd9zeHxhDSKYZ0aF0/s320/figure9.png" width="320" /></a></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><span class="st"><span class="st">Another important question that could be raised in regard of the reliability of the inferred components is the question of 'component purity' (the notion of 'purity' is used here in rather speculative sense of Kant's <i>Reinheit</i>, and has nothing to do with 'racial purity'). Indeed, a population tree (such as one presented above) could represent </span></span><span class="st"><span class="st"><span class="short_text" id="result_box" lang="en"><span class="hps">with the same degree</span> <span class="hps">of reliability</span></span> both <span class="st"><i>pure nested</i> morphology of components variable <i>component</i>s of <i>nested</i> and non-nested morphology.</span></span></span></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">Fortunately for genome bloggers, we can try to tackle this problem by using three- and four- population tests for treeness from <a href="http://www.nature.com/nature/journal/v461/n7263/abs/nature08365.html" rel="nofollow">Reich et al. 2009</a>. The 3-population test (<a href="http://www.nature.com/nature/journal/v461/n7263/full/nature08365.html">Reich et al. 2009</a>) allows one to detect the presence of admixture in a population X from two other populations A and B. The value</span>
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f3(X; A, B)</span></div>
<span style="font-family: "Trebuchet MS",sans-serif;"><br />is negative when X does not appear to form a simple tree with A and B but appears to be a mixture of A and B (in Dienekes'<a href="http://dienekes.blogspot.com/2012/08/3-population-test-and-east-eurasian.html"> laconic phrasing</a>). In order to calculate f3 statistics i used the implementation of <i>three-pop </i> <a href="https://code.google.com/p/treemix/">TreeMix's </a> program threepop:</span><br />
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<span style="font-family: "Trebuchet MS",sans-serif;"><b>X A,B</b></span><br />
<span style="font-family: "Trebuchet MS",sans-serif;">Samoedic North-Siberean,Atlantic_Mediterranean_Neolithic 0.00206352 0.000146163 14.118<br />North-Amerind South-America_Amerind,South-African 0.00564354 0.00034763 16.2344<br />Samoedic North-Siberean,North-East-European 0.00230317 0.000134738 17.0936<br />North-Amerind South-America_Amerind,Melanesian 0.0063216 0.000345733 18.2846<br />Sub-Saharian South-America_Amerind,South-African 0.0058646 0.000302046 19.4162<br />Sub-Saharian Pygmy,South-America_Amerind 0.00420139 0.000216014 19.4496<br />Sub-Saharian Pygmy,Paleo-Siberean 0.00426537 0.000217229 19.6354<br />Sub-Saharian Pygmy,North-Siberean 0.00438367 0.000221767 19.767<br />North-Amerind Pygmy,South-America_Amerind 0.0058802 0.000295087 19.927<br />Sub-Saharian Pygmy,Mesomerican 0.00439921 0.000219885 20.0068<br />Sub-Saharian Pygmy,Arctic-Amerind 0.00427798 0.000212131 20.1667<br />Samoedic South-America_Amerind,South-African 0.00679588 0.000332084 20.4643<br />North-Amerind South-America_Amerind,Austronesian 0.00658824 0.000314661 20.9375<br />Samoedic North-Siberean,South-African 0.00504898 0.000240205 21.0195<br />North-Amerind South-America_Amerind,Paleo-Siberean 0.00580508 0.000275451 21.0748<br /> </span><br />
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<span style="font-family: "Trebuchet MS",sans-serif;">The full f3statistics file could be downloaded <a href="https://docs.google.com/spreadsheet/ccc?key=0Aqn7iMc2P-yQdElGcUxENkhlRUtrVFVFQXMtZXpLU3c">here</a>.</span><br />
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<span style="font-family: "Trebuchet MS",sans-serif;">After the careful examination of f3statistics for 22 putative ancestral components, i haven't found negative values (negative value is a strong unambiguous signal of admixture). Thus, we could safely reject the hypothesis of mixture in ancestral components, and assume that each X components forms a simple tree with A and B components.</span><br />
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Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com0tag:blogger.com,1999:blog-7120134997435393696.post-30627813600927668362012-09-15T08:00:00.003-07:002012-09-15T10:21:02.934-07:00Behind the Curtains: MDLP World 22 showcase<div dir="ltr" style="text-align: left;" trbidi="on">
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<span style="font-family: "Trebuchet MS",sans-serif;"><b>Preliminary remarks</b><br /><br />As you all may know, the MDLP blog hasn't been updated since February 2012.</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">Half of year ago i promised myself that i would stop writing new posts on the MDLP blog before i'll finally get my scientific report on blog written. Since I had to prioritize the completion of a scientific paper over the routine of blog posting,<span class="stream _p _pl1 _pd581279" id="view"><span class="mtxt">I was unable to continue updating the blog on a regular basis due to a lack of time, and had to make<i> </i><span class="st">a change in how I conducted my research. So i decided to abstain from posting on the MDLP blog for a couple of month, being focused on more important matters. Despite of all limitations, i kept working secretly on the MDLP project, collecting necessary data and performing different 'genomic' experiments in order to achieve my final goal (publishing of paper). The results of secret experiments with new genomic samples and tools eventually leaked to the curious public, spawning </span></span></span><span class="st">immense interest in my project. After releasing a new version of my own modification of <a href="http://dodecad.blogspot.com/2011/09/do-it-yourself-dodecad-v-21.html">DIYDodecad calculator</a></span> on <a href="http://www.gedmatch.com/">Gedmatch.com</a>, i was literally flooded by emails from Gedmatch.com users asking me questions they wanted me to answer. <br /><br />I understood the strategical mistake of releasing poorly documented data/analysis on Internet and felt obliged to explain details. Obviously, i will start new series of the blog posts by covering the project feature the people most interested in, i.e the MDLP World22 calculator.<br /><b> </b></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><b>The population dataset</b> <b>of MDLP World22 calculator.</b></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">The reference population dataset of the calculator was assembled in <a href="http://pngu.mgh.harvard.edu/~purcell/plink/">PLINK</a> by intersecting and thinning the samples from different data sources: <a href="http://www.sanger.ac.uk/resources/downloads/human/hapmap3.html">HapMap 3</a> (the filtered dataset CEU,YRI,JPT,CHB), <a href="http://1000 Genomes Project">1000genomes</a>, <a href="http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE22494">Rasmussen et al. (2010)</a>, <a href="http://hagsc.org/hgdp/files.html">HGDP (Stanford) (all populations)</a>,
<a href="http://dienekes.blogspot.com/2011/12/population-structure-in-south-asia.html">Metspalu et al. (2011)</a>,<a href="http://www.evolutsioon.ut.ee/MAIT/caucasus_data/">Yunusbayev et al. (2011)</a>, <a href="http://mbe.oxfordjournals.org/content/early/2010/10/26/molbev.msq288.short">Chaubey et al. (2010)</a> etc. Furthermore i handpicked random 10 individuals from each European country panel in POPRES dataset, or the maximum number of individuals available
otherwise, to select the POPRES European individuals to be included in our study. Finally, in order to evaluate the correlation between the modern and the ancient genetic diversity, i have also included ancient DNA genomic samples of <a href="http://www.ebi.ac.uk/ena/data/view/ERP001144">Ötzi,</a>(<a href="http://www.nature.com/ncomms/journal/v3/n2/full/ncomms1701.html">Keller et al.(2012</a>)) Swedish Neolithic samples Gök4, Ajv52, Ajv70, Ire8, Ste7 (<a href="http://dienekes.blogspot.com/2012/04/ancient-dna-from-neolithic-sweden.html">Skoglund et al. (2012)</a>) and 2 <a href="http://biologiaevolutiva.org/~clalueza/repository/">La Bra<span style="background-color: white;">ñ</span></a><span style="background-color: white;"><a href="http://biologiaevolutiva.org/~clalueza/repository/">a individuals</a> from the Mesolithic sites of the Iberian Peninsula (</span><span style="background-color: white;"><span style="font-size: 100%;"><a href="http://www.blogger.com/"><span id="goog_406839859"></span>Sánchez-Quinto et al.(2012<span id="goog_406839860"></span></a>)</span>). Then i added 90 samples of individuals-participants of our MDLP project. <b> </b></span>After merging the aforementioned datasets and thinning the SNP set with PLINK command to exclude SNPs with missing rates greater than 1% and minor alleles, i filtered out duplicates, the individuals with high pairwise IBD-sharing (estimated in Plink as as the average fraction of alleles shared
between two individuals over all loci) and the individuals with kinship coefficient suggesting relatedness (kinship coefficients were estimated in <a href="http://bioinformatics.oxfordjournals.org/content/26/22/2867.full">KING software</a>). Also i had to filter out individuals with more more tham 3 standard deviations from the population averages. Since kinship coefficient is robustly estimated by HWE (Hary-Weinberg expectations) among SNPs with the same underlying allele frequencies, SNPs showing strong deviation (<i>p</i> < 5.5 x10<sup>−8</sup>) from Hardy-Weinberg expectations were removed from the merged and filtered dataset. After that I filtered to keep the list of common SNPs present in Illumina/Affymetrix chips and performed </span><span style="font-family: "Trebuchet MS",sans-serif;"> linkage disequilibrium based pruning using a window size of 50, a step of 5 and r^2 threshold of 0.3.</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><br />This complex sequence of consequent operations with the initial reference and project datasets yielded a final dataset which included 80751 SNPs in 2516 individuals from 225 populations.<br /><br /><br />ADMIXTURE analysis</span><br />
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<span style="font-family: "Trebuchet MS",sans-serif;"> </span><span style="font-family: "Trebuchet MS",sans-serif;">As always, the final dataset in PLINK linked format was further processed in <a href="http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CCAQFjAA&url=http%3A%2F%2Fwww.genetics.ucla.edu%2Fsoftware%2Fadmixture%2Fadmixture-manual.pdf&ei=KHFUULDcIvPa4QSH2oCYAg&usg=AFQjCNEH4uYnO-4psokVChGNVGYSchE3hw">ADMIXTURE </a>software. Sketching the plan for the design of ADMIXTURE test, i had to face the difficult problem: as it has been shown in (<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.0020190">Patterson et al.2006</a>) the number of markers needed to resolve populations in ADMIXTURE analysis is inversely proportional to the genetic distance (Fst ) betweeen the populations. According to ADMIXTURE best practice, it is believed that 10,000 markers are suffice to perform GWAS correction for continentally separated populations (for example, African, Asian, and European pop</span><span style="font-family: "Trebuchet MS",sans-serif;">ulations FST > .05) while more like <u><b>100,000 markers are necessary when the populations</b></u></span><u><b><span style="font-family: "Trebuchet MS",sans-serif;"> are within a continent (Europe, for instance, FST < 0.01).</span></b></u></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">To increase the accuracy of ADMIXTURE results i decided to use a method proposed by Dienekes' <a href="http://dodecad.blogspot.com/2011/05/how-to-create-zombies-from-admixture.html">for converting allele frequencies into 'synthetic individuals'</a>(see also<a href="http://www.harappadna.org/2011/07/admixture-supervised-zombies-vs-unsupervised/"> Zack's example</a>). </span><span style="font-family: "Trebuchet MS",sans-serif;">The idea is fairly simple: run an unsupervised ADMIXTURE analysis <i>once </i>to
generate allele frequencies for your K ancestral components; then
generate zombie populations using these allele frequencies; whenever you
want to estimate admixture proportions in new samples run supervised
ADMIXTURE analysis using the zombie populations. Like any genome blogger engaged in the task of evaluating admixtures in samples, i must grapple with obvious question of the reliability of this approach. Although i am aware of methodological controversies in using simulated individuals, i would rather concur with Dienekes who considered "synthetic individuals" the best abstract proxies for the ancient ancestral populations. But my purpose is served if i can use the approach used by Dienekes and Zack to obtain meaningful results. To begin with, i routinely ran unsupervised ADMIXTURE K=22 analysis (assuming 22 ancestral populations) which yielded the <b>admixture proportions </b>of individuals from these K populations, as well as the <b>allele frequencies </b>for all SNPs for each of 22 ancestral populations (below are conventional names for each of inferred components in order of appearance):</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><b>Pygmy<br />West-Asian<br />North-European-Mesolithic<br />Tibetan<br />Mesomerican<br />Arctic-Amerind<br />South-America_Amerind<br />Indian<br />North-Siberean<br />Atlantic_Mediterranean_Neolithic<br />Samoedic<br />Proto-Indo-Iranian<br />East-Siberean<br />North-East-European<br />South-African<br />North-Amerind<br />Sub-Saharian<br />East-South-Asian<br />Near_East<br />Melanesian<br />Paleo-Siberean<br />Austronesian</b></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;">Therefore i took the allele frequencies which were computed earlier in unsupervised Admixture K=22 for the merged dataset, pooled them into PLINK and generated 10 "synthetic individuals per ancestral component) using PLINK command -<i>-simulate</i>. When the simulation had been finished, i visualized the distance between simulated individuals using multi-dimensional scaling:<br /><br /> </span><br />
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<span style="font-family: "Trebuchet MS",sans-serif;"></span><span style="font-family: "Trebuchet MS",sans-serif;"> As a next step,i included simulated individuals you have as part of a new reference population (including 220 simulated individuals in 22 simulated populations).Then, I ran ADMIXTURE anew, this time in “supervised” mode for K = 22 (with simulated individuals being 'reference' individuals). The Admixture K=22 converged in 31 iterations (37773.1 sec) with final loglikelihood:-188032005.430318 (below are Fst divergences between estimated 'ancestral' populations):</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><br />The Fst distance/divergence matrix was used for inferring a most probable NJ-based topology of component distance tree (outgroup: South-African):</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"> The individual 'supervised' ADMIXTURE <a href="https://docs.google.com/spreadsheet/ccc?key=0Aqn7iMc2P-yQdHVaM1dGWHNLcjcxWGZVTkt0OEdfcFE#gid=0">results (in Excel spreadsheet)</a> for the project participants have been uploaded to GoogleDocs (please note that the average results for reference populations is also available on special request). </span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><b>MDLP World22 DIYcalculator</b><br /><br />The output files of <u><b>Admixture K=22 supervised run</b></u> (average values of admixture coefficients in reference populations and FsT values) were used for designing a new version of the MDLP DIYcalculator, which is better known by its codename "World22" (online version is available in AdMix-Utilities section of <a href="http://ww2.gedmatch.com:8006/autosomal/ap_mix1_gen.php">Gedmatch</a> under MDLP project). MDLP DIYcalculator itself is based on the code of Dodecad DIY calculator (c)ourtesy of <a href="http://dienekes.blogspot.com/">Dienekes Pontikos</a> and was developed as part of the <a href="http://dodecad.blogspot.com/">Dodecad Ancestry Project</a>. In its Gedmatch implementation MDLP 'World22' DIYcalculator is paired by MDLP 'World22' Oracle, also based on Dienekes' and Zack's code (<a href="http://www.harappadna.org/2012/03/harappa-oracle/">Harappa/DodecadOracle</a>). The 'Oracle' is designed to find in<b> a single population mode</b> your closest (closest in terms of similarity) population from MDLP ''Word22' admixture results. In <b>a mixed mode</b>, Oracle considers all pairs of populations, and for each one of
them calculates the minimum <b>Fst-weighted</b> distance to the sample in consideration,
and the admixture proportions that produce it.</span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><br /><b>Please notice: 'ancestral' populations (i.e 'simulated populations' from the previous step - see above) are labeled in Oracle results as (anc), while the 'real world' modern and ancient populations are marked as "derived". </b><br /><br />If you have troubles with understanding/interpreting the results of Oracle and DIYcalculcator, please consult the corresponding topics on Dodecad and HarappaWorld blogs. It is not of avail to repeat in this blog everything they wrote in their own blogs.</span></div>
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<b><span style="font-family: "Trebuchet MS",sans-serif;">What the heck are MDLP Word-22 components?</span></b></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"> One of those questions that i usually keep getting in emails is what do the various reference populations and ancestral components for my World K=12 and World-22 analyses mean. I've already provided hints to the answer earlier, but - as old Chinese proverb says - one picture is worth ten thousand words. That's why i decided to display the admixture coefficients spatially on the globe surface. Following Francois Olivier, who <a href="http://membres-timc.imag.fr/Olivier.Francois/admix_display.html">proposed</a> to use the graphical library of the
statistical software R to display spatial interpolates of
the admixture coefficients (Q matrix) in two dimensions (where </span><span style="font-family: "Trebuchet MS",sans-serif;">spatial coordinates are recorded as longitude and latitude), i created 2 contour maps per component.<br /><br /> <b>Pygmy (modal in Biaka and Mbuti population)</b></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><b>West-Asian (bimodal component with peaks in Caucasian populations and south-western part of Iran, equal to Dienekes' Caucasian/Gedrosia component) </b></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><b> <span style="font-family: "Trebuchet MS",sans-serif;"><b>North-European-Mesolithic (local component with peaks in European Mesolithic samples of La_Brana and modern North-European Saami population).</b></span></b></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"> <span style="font-family: "Trebuchet MS",sans-serif;"><b>Tibetan (Indo-Burmese) component (Himalay, Tibet)</b></span></span></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"><b>Mesomerican (major genetic component in Native Americans from Mesoamerica)</b></span><br />
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<span style="font-family: "Trebuchet MS",sans-serif;"><b>North-Amerind (the 'native' component in North American Natives)</b></span><br />
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<span style="font-family: "Trebuchet MS",sans-serif;"><b>South-Amerind (the 'native' component in South American Natives)</b></span></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi0jBwL1hH1TgAnl9AX6phSBTx-N5Q95bQ30Nvl7LXkvvKjPQBVvp3Kb00qPo-MRoLn3C_KKc1EmNyj1Xfa1_IfNhcyi4SrlPLo2YBLuKPWa-1H16if2wVNOweGJArJ4TM1pUOBUS1F5RA/s1600/South-America_Amerind.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi0jBwL1hH1TgAnl9AX6phSBTx-N5Q95bQ30Nvl7LXkvvKjPQBVvp3Kb00qPo-MRoLn3C_KKc1EmNyj1Xfa1_IfNhcyi4SrlPLo2YBLuKPWa-1H16if2wVNOweGJArJ4TM1pUOBUS1F5RA/s320/South-America_Amerind.png" width="317" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgIhkSpMyS2PGm-G-vyB9Eq5blDf0bFyPvaAQqO1myrV12V5caWYjZpJJzRFf4NGpD4HNFdfA96gSLyZle5m2HvfVGO7Kr0PDpo9q3uuLsbSehsk_X2k5wzNLqliu0aIBKjNbu5Sgf7hSg/s1600/South-Amerind-1.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgIhkSpMyS2PGm-G-vyB9Eq5blDf0bFyPvaAQqO1myrV12V5caWYjZpJJzRFf4NGpD4HNFdfA96gSLyZle5m2HvfVGO7Kr0PDpo9q3uuLsbSehsk_X2k5wzNLqliu0aIBKjNbu5Sgf7hSg/s320/South-Amerind-1.png" width="317" /></a></div>
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<span style="font-family: "Trebuchet MS",sans-serif;"> Atlantic-Mediterranean-Neolithic (the main genetic component in Western and South-Western Europe)</span></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhTuWUz0m90Y6P21Tqd15sXPQIGDzX5-lVe2CE08IjReh2fvYDIPtFgcPrsI-qhXoZBgH5CRbkJTDsquk-WOfHOlm9u9s7mxGhGy2KXqsdfmODqFUFr-lZN6yuc6we0MoptK19cS-mzIWI/s1600/Atlantic_Mediterranean_Neolithic-1.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhTuWUz0m90Y6P21Tqd15sXPQIGDzX5-lVe2CE08IjReh2fvYDIPtFgcPrsI-qhXoZBgH5CRbkJTDsquk-WOfHOlm9u9s7mxGhGy2KXqsdfmODqFUFr-lZN6yuc6we0MoptK19cS-mzIWI/s320/Atlantic_Mediterranean_Neolithic-1.png" width="317" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj4gsYyEYDVxWAMkv_Fh87CukLD45FbSmFhjwgJAVwbsx6Xk0dQk1oMNIp0fSwGKTR9sUxiOjiy9zuTjfXDpo_-xSmLeSz6Ers9o_xnVHf2vz_p2sxse7An0gpdxwOpemo0R8UlNn0cwGE/s1600/Atlantic_Mediterranean_Neolithic.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj4gsYyEYDVxWAMkv_Fh87CukLD45FbSmFhjwgJAVwbsx6Xk0dQk1oMNIp0fSwGKTR9sUxiOjiy9zuTjfXDpo_-xSmLeSz6Ers9o_xnVHf2vz_p2sxse7An0gpdxwOpemo0R8UlNn0cwGE/s320/Atlantic_Mediterranean_Neolithic.png" width="317" /></a></div>
<span style="font-family: "Trebuchet MS",sans-serif;"><br /> The rest contour maps for all components could be<a href="https://docs.google.com/open?id=0B6n7iMc2P-yQNGFYVVVOc3FhSUk"> downloaded here</a>.<br /><br /><br /><br /><br /><span class="stream _p _pl1 _pd581279" id="view"><span class="mtxt"><span class="st"><br /><br /> </span></span></span> </span></div>
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Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com33tag:blogger.com,1999:blog-7120134997435393696.post-47632056591597214402012-09-10T15:14:00.001-07:002012-09-10T15:14:08.849-07:00Rising from The Ruins<div dir="ltr" style="text-align: left;" trbidi="on">
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The MDLP blog is back online again.<br />
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Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com1tag:blogger.com,1999:blog-7120134997435393696.post-18314055861216619372012-01-21T05:41:00.000-08:002012-01-23T03:18:42.291-08:00Comparing fineSTRUCTURE clustering to Mclust clusterings<div dir="ltr" style="text-align: left;" trbidi="on">
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgDmDpADR5c-TegUPDJL03ldvY_a5TMpY0nlu0IuKTeKuHN1BPE2yb_53lSdor84V1F10FtlcQvHdOxl-zcA6X-BYFhJwR-Y3Zxv0jMachpT00LfApyMATJ_tMEUDr9Fc9Gr10ZyMqczM8/s1600/uncertain.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgDmDpADR5c-TegUPDJL03ldvY_a5TMpY0nlu0IuKTeKuHN1BPE2yb_53lSdor84V1F10FtlcQvHdOxl-zcA6X-BYFhJwR-Y3Zxv0jMachpT00LfApyMATJ_tMEUDr9Fc9Gr10ZyMqczM8/s320/uncertain.png" width="320" /></a></div>
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The first weeks of 2012 years marked a milestone in BGA blogging paradigm , introducing substantial shift of methodologies.</div>
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First of all,<a href="http://bga101.blogspot.com/2012/01/eurogenes-north-euro-clusters-phase-1.html"> Eurogenes blog</a> has applied recently published Chromopainter tools to its <span style="font-size: 100%;">intra-North Euro cluster analysis (</span><span style="font-size: 100%;">with more than
400 samples and 270K SNPs, in linkage mode, and 200K burn-ins and iterations).</span></div>
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<a href="http://www.blogger.com/goog_74269422"><br /></a></div>
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<span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: Georgia,"Times New Roman",serif;"><a href="http://dodecad.blogspot.com/">Dodecad Project</a> has also improved its <a href="http://dienekes.blogspot.com/2012/01/clusters-galore-fastibd-edition.html"> Cluster Galore method </a>to be used with linked haplotype data (this refined method is , however, designed, to work not wiyj fineSTRUCTURE, but with different software fastIBD).</span></span></span></div>
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<span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: Georgia,"Times New Roman",serif;">Although both methods are different in technical performance and design, they still strive for the same goal of inferring the population structure. This type of structure inference consists of two parts: deriving a matrix of relationships between sampled individuals and clustering these relationships. <a href="http://www.maths.bris.ac.uk/%7Emadjl/finestructure/comparisons.html">As was noted by Dan Lawson</a> , given a distance-like matrix such as the number of SNPs IBS or the ChromoPainter coancestry matrix, it is possible to apply<b> a wide variety of clustering algorithms. </b></span></span></span></div>
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<b><span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: Georgia,"Times New Roman",serif;">Still fineSTRUCTURE has two advantages. Firstly, because fineSTRUCTURE performs MCMC it is less likely to get stuck in local optima than computationally cheaper methods that climb gradients. Secondly, and most importantly, (when used correctly) fineSTRUCTURE is well calibrated as it has no unknown and hard to estimate tuning parameters. </span></span></span></b></div>
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<u><b><span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: Georgia,"Times New Roman",serif;">Experiment</span></span></span></b></u></div>
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<span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: Georgia,"Times New Roman",serif;">In order to evaluate the performance of different clustering methods on a real-world dataset, i used sampled individuals from my project. To make this test experiment even harder, i've applied Chromopainter's algorithm (*linkage mode) to a homogenous uniform subset of very similar Baltic Populations: Lithuanians, Belorussians, Ukrainians (90 samples plus a couple of reference Belorussian, Lithuanian and Ukrainian samples with 90K SNPs). The same dataset was used in Shellfish to carry out a principal component analysis of genome-wide SNP data, and in PLINK MDS-calculations. Obtained PCA and MDS data was subsequently analyzed using the general-purpose clustering software Mclust.</span></span></span></div>
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<span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: Georgia,"Times New Roman",serif;">I ran Chromopainter's algorithm separately on each of 22 chromosomes, the output files were merged into one single file. Then i applied fineSTRUCTURE's MCMC algorithm to infer the population structure, PCA components and cluster trees. Below are plots showing individual co-ancestry matrix, individual and population agglomerate plots and PCA plots.</span></span></span></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiwivMKRvgkHd8aaswJfa73K1kWkiNkXpRQYBqx30o8xbsMEEAfEDQk2sNsiHPyyYnrmpOl3L452yFurKwqIocRGoC_7dsiWfJ5lE1wnpSgXsqsz6ttvWlvgWyIpdifmO_MXliZ0k3y600/s1600/indiv-coancestry.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="288" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiwivMKRvgkHd8aaswJfa73K1kWkiNkXpRQYBqx30o8xbsMEEAfEDQk2sNsiHPyyYnrmpOl3L452yFurKwqIocRGoC_7dsiWfJ5lE1wnpSgXsqsz6ttvWlvgWyIpdifmO_MXliZ0k3y600/s320/indiv-coancestry.png" width="320" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgi0ZNgTBEJ3PZPurg4WX-oLpPM2uXYIW7MrY0zDPyZh10WsQizo5onpXxK2vWXQHrcPAnALAW24yE_igtKV9HZXhL5hK7WPy7bPnff5QVP-UV_YB6jTPXTkqgcqDW5_Od7NY7wCVxyrlk/s1600/aggregate.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="288" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgi0ZNgTBEJ3PZPurg4WX-oLpPM2uXYIW7MrY0zDPyZh10WsQizo5onpXxK2vWXQHrcPAnALAW24yE_igtKV9HZXhL5hK7WPy7bPnff5QVP-UV_YB6jTPXTkqgcqDW5_Od7NY7wCVxyrlk/s320/aggregate.png" width="320" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEimt6YdgWoQWMIf-vwThQ7_F7Kqg5WvGVZQo3FXnItZqdrAFI5cWdZ-NNIsUO7zTw3r_ytwr3BLNr-mccFoWaMBaomem0TuKm8fARdFY7IRpJfblNGR7XpAPapupcA3vIK0gPxe8GTLDVg/s1600/aggregate2.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="288" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEimt6YdgWoQWMIf-vwThQ7_F7Kqg5WvGVZQo3FXnItZqdrAFI5cWdZ-NNIsUO7zTw3r_ytwr3BLNr-mccFoWaMBaomem0TuKm8fARdFY7IRpJfblNGR7XpAPapupcA3vIK0gPxe8GTLDVg/s320/aggregate2.png" width="320" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhQEOdOQFOG7NaTPdIcSGZa3WyWgHfxwEM4KnFmGgvgJlO92MdG_gu_FUEzH1j8hKbdOJOOdqTENmiR499x4n1_guOka2yp_TxbEk9C6aNHwdcE0nV-Ns0Jhal7fQxL8H9aoXeaSp2BuOo/s1600/PCA.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhQEOdOQFOG7NaTPdIcSGZa3WyWgHfxwEM4KnFmGgvgJlO92MdG_gu_FUEzH1j8hKbdOJOOdqTENmiR499x4n1_guOka2yp_TxbEk9C6aNHwdcE0nV-Ns0Jhal7fQxL8H9aoXeaSp2BuOo/s320/PCA.png" width="320" /></a></div>
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<span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: Georgia,"Times New Roman",serif;">It appears that fineSTRUCTURE inferred 5 clusters (starting with smallest): (1) Ashkenazi, (2) individuals of West-European origin with (moderate to minor) East-European "admixture" (3) individuals from East-Europe and <b>(4) Lithuanians, (5) the biggest cluster including Poles, </b></span></span></span><span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: Georgia,"Times New Roman",serif;"><b>Belorusians, Russians and Ukrainians. </b></span></span></span><span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: Georgia,"Times New Roman",serif;"><b></b></span></span></span><br />
<span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: Georgia,"Times New Roman",serif;">For our project's particular purposes, it is important to note that such a clear split between Belorussians and Lithuanians is introduced for the first time. Although the innuendo of this division could be inferred from our earlier experiments, the statistical signal of separation was weak enough to be ignored, because (as it is shown on the plot below) some regions of the plots are highly uncertain.</span></span></span><br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgDmDpADR5c-TegUPDJL03ldvY_a5TMpY0nlu0IuKTeKuHN1BPE2yb_53lSdor84V1F10FtlcQvHdOxl-zcA6X-BYFhJwR-Y3Zxv0jMachpT00LfApyMATJ_tMEUDr9Fc9Gr10ZyMqczM8/s1600/uncertain.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgDmDpADR5c-TegUPDJL03ldvY_a5TMpY0nlu0IuKTeKuHN1BPE2yb_53lSdor84V1F10FtlcQvHdOxl-zcA6X-BYFhJwR-Y3Zxv0jMachpT00LfApyMATJ_tMEUDr9Fc9Gr10ZyMqczM8/s320/uncertain.png" width="320" /></a></div>
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<span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: Georgia,"Times New Roman",serif;">The cluster assignments (fineStructure) for project's individuals can be seen <a href="https://docs.google.com/spreadsheet/ccc?key=0Aqn7iMc2P-yQdEV5ZElZandnZ3JfVjdqM2V6eXI0bmc">here.</a></span></span></span><br />
<span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: Georgia,"Times New Roman",serif;"> I have also published corresponding cluster assignments by Mclust (<a href="https://docs.google.com/spreadsheet/ccc?key=0Aqn7iMc2P-yQdGdfN0ZZYUtfeFMzWFhlbWF6ZGFHQ1E">PLINK+MClust</a> and <a href="https://docs.google.com/spreadsheet/ccc?key=0Aqn7iMc2P-yQdDNYMXZ3eC1RRzBPVDNjUTRHNVFWMlE">Shellfish+MClust</a>). Direct agreement between these two latter solutions: 0 of 4 pairs, iterations for permutation matching: 24, cases in matched pairs: <b>34.58</b> %<br /><br /> 2 3 1 4<br /> 1 0 2 3 0<br /> 2 2 8 1 3<br /> 3 13 11 16 18<br /> 4 4 4 9 13</span></span></span><br />
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<span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: Georgia,"Times New Roman",serif;"><b> </b></span></span></span><span style="font-size: 100%;"><span style="font-family: arial;"><span style="font-family: Georgia,"Times New Roman",serif;"> </span></span></span></div>Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com19tag:blogger.com,1999:blog-7120134997435393696.post-70020482799730533682011-12-29T13:31:00.000-08:002012-01-08T10:17:44.445-08:00Last posting in the year 2011<div dir="ltr" style="text-align: left;" trbidi="on">
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Earlier this month I experimented with <a href="http://www.paintmychromosomes.com/">Chromopainter and fineSTUCTURE</a> software. For
the sake of comparision with ADMIXTURE/LAMP results, i used PLINK
linkage file with previously extracted SNPs on Chr.6. The PLINK file
included thinned set of LD-pruned SNPs (9155 SNPs in total). I also
limited the dataset to include the projectäs participants only. I
streamlined the phasing of this dataset by using Gusev's <a href="http://www.cs.columbia.edu/%7Egusev/germline/">phasing_pipeline</a> (which is indispensable for conversion between PLINK and BEAGLE format, and phasing genotypes with BEAGLE).<br />
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After that i deployed plink2chromopainter.pl, a conversion script for
going from PLINK linkage-style PED and MAP files to ChromoPainters PHASE
and MAP files. The converted MAP file was merged with HapMap's
pre-compiled recombination file for Chr.6 (in order to accomplish this
task i used a simple buggy but efficient AWK script). This trick allowed
me to avoid/skip the painstaking exercise in UNLINKED model of
Chromopainter <img alt="" border="0" class="inlineimg" src="http://www.forumbiodiversity.com/images/smilies/smile.gif" title="Smile" /> .<br />
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As a next step, i changed default -k parameter to 200 (to give
approximately 200 random samples to estimate the local variance). It is
important to mention, that Chromopainter could be run in two modes:
"donor mode" (which assumes the prior existence of "donor" and
"recipient" haplotypic populations) and "all against all" mode. I we
used the latter approach in which a single haplotype within an
individual is reconstructed using the haplotypes from <b>all other individuals</b>
in the sample as potential donors. This process is repeated for every
haplotype in turn, so every individual is ultimately reconstructed in
terms of all the other individuals, i.e every individual in my sample
is conditioned on all the other individual.<br />
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It took me approximately 1,45 hours to finish Chromopainter's job. After
that in combined Chromopainter output files, creating the file
"MDLP.Chr6.chunkcounts.out", which is the coancestry matrix that
fineSTRUCTURE requires as input.<br />
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After that i fed fineSTRUCTURE with required input (the coancestry
matrix) and let fineSTRUCTURE to find a correct number of sample's
"splits" (clusters). Surprisingly, even in such a limited (LD-prunned
and tiny) dataset of SNPs, fineSTRUCTURE was able to detect four
population-like (2 East-European, 1 West-European and outliers)
clusters. In comparision, ADMIXTURE had some troubles with fleshing out
sample's K-clusters, when i ran it on both phased and unphased version
of the same Chr6. dataset (you can see them in this <a href="https://docs.google.com/spreadsheet/ccc?key=0Aqn7iMc2P-yQdFZOR0p5bHdXRG44bjVVaEdlVktHTmc" target="">Excel spreadsheet</a>). </div>
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From what i gather, author's claim holds water: fineSTRUCTURE indeed outperform ADMIXTURE/STRUCTURE approaches: "We next turn to our fineSTRUCTURE model-based analysis, again
considering the unlinked coancestry matrix even though strong and
variable LD exists in the dataset. <b><u>We first compared performance
of our unlinked model to the popular ADMIXTURE [15] software (Figure 3B
and D, details in Section S8). Encouragingly, as the number of 5Mb
regions increased from 5 to 200 we saw a monotonic performance increase
for the no-linkage model, separating all groups with 200 markers.
Further, our approach outperformed ADMIXTURE, with the ADMIXTURE
performance levelling at around 60% correlation with the truth.</u></b>
In practice, we observed ADMIXTURE successfully splitting groups A, B
and C and mostly splitting C1 and C2, but not B1 and B2, as detailed in
Figures S6-11. ADMIXTURE performs inference under a model where markers
are treated as unlinked, and where individuals may have genomes made up
of mixtures of inferred source populations, while our simulation
incorporated drift between populations, but not admixture. To examine
whether violations of both these modelling assumptions explain the
different results, we simulated a new dataset with the same underlying
population structure of 5 populations as before, but no linkage (i.e.
independence) between markers within each population. We analysed these
data with STRUCTURE, which uses a similar underlying model to that of
ADMIXTURE, but includes a no-admixture model (Section S7). <b><u>For
small datasets, STRUCTURE slightly improved performance relative to our
unlinked fineSTRUCTURE model, but for larger SNP numbers, fineSTRUCTURE
was able to identify all population splits (K = 5) while again,
STRUCTURE was able to split only populations A, B and C (K = 3)</u></b>.
Thus, even when LD information is not used (or even present),
fineSTRUCTURE can offer advantages in some settings over these existing
approaches."
</div>
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With this gist of fineSTRUCTURE methodology, is is now safe to conclude
that the combined set of all 22 chromosome, the linkage model can do
even better. </div>
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The painting process gives three square matrices of size NxN (N=number of individuals): 1) the frequency individuals copy chunks from each other, 2) the average length of those chunks, and 3) the mutation rate. These contain different aspects of the ancestry history, and almost completely summarize population ancestry. </div>
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The origin of some individual haplotypes could be ascertained using more comprehensive GERMLINe matching algorithm. Indeed, after applying GERMLINE algorithm to BEAGLE-phased chromosomes
(1..22), i can see that the pairwise matches in haplotypes located far
away from the chromosomal centromere and telomeres, tend to cluster into
"ethnic" groups. However, haplotypes which are observed near
centromere, are rather omnipresent - as would be expected if these
regions had low rates of recombination because of proximity to
centromeres. The IBD segments detected by GERMLINE are listed (per chromosome) below:</div>
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<a href="https://docs.google.com/leaf?id=0B6n7iMc2P-yQZjkxNWNhNmMtZjUwYy00Yjk5LWJmNzItMDM5ZTY5N2QzYWVl&hl=en_US">Chromosome12</a></div>
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<a href="https://docs.google.com/leaf?id=0B6n7iMc2P-yQZWM5MjM5ZDQtZTAwMy00ZTVhLTk0OGItNmUyNjdmMjAwOGRl&sort=name&layout=list&num=50">Chromosome11 </a></div>
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<a href="https://docs.google.com/leaf?id=0B6n7iMc2P-yQZTRkZDhmNDEtZDlmNS00YzFhLWFjM2UtZTJhODJiMGRlZjI2&sort=name&layout=list&num=50">Chromosome13</a></div>
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<a href="https://docs.google.com/leaf?id=0B6n7iMc2P-yQYzA4Y2I4NGEtOTY3MC00Y2Y2LTlhMzEtM2QwNDE2MmZlYTRh&sort=name&layout=list&num=50">Chromosome14</a></div>
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<a href="https://docs.google.com/leaf?id=0B6n7iMc2P-yQOWEwZGYzNWUtZjcwMi00YmRmLTk4NTUtZTE5Zjc4NzI0YWJm&sort=name&layout=list&num=50">Chromosome19</a></div>
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<a href="https://docs.google.com/leaf?id=0B6n7iMc2P-yQOTIyMTI3YjQtYWJhOS00NWQ2LTllM2EtYWI2ZGQyMTNhYjA0&sort=name&layout=list&num=50">Chromosome15</a></div>
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<a href="https://docs.google.com/open?id=0B6n7iMc2P-yQOGEyMWU1YWQtOTJiYy00YTU3LWEwNDctN2U4YTg3MGMzYjVl">Chromosome20</a></div>
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<a href="https://docs.google.com/open?id=0B6n7iMc2P-yQNjRkNDUxNGEtOGVkZi00NWFhLTkyYTMtMzk2OWRiZTJkM2Q3">Chromosome9</a></div>
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<a href="https://docs.google.com/leaf?id=0B6n7iMc2P-yQMzVkYmRiYTYtMmE1Ny00ODFhLTg4MDItNGIwMTE1ZDc3ZjE1&sort=name&layout=list&num=50">Chromosome8</a></div>
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<a href="https://docs.google.com/leaf?id=0B6n7iMc2P-yQMjk5ZWMzMTYtZjM1OS00ZjM3LWE5NWEtZjhhNjE2MjUwM2Jh&sort=name&layout=list&num=50">Chromosome18</a></div>
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<a href="https://docs.google.com/leaf?id=0B6n7iMc2P-yQMWViNTUzOWUtNTlmNi00MDQ2LTgyZDktMGU4MTc4MTEyZDI3&sort=name&layout=list&num=50">Chromosome21</a></div>
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<a href="https://docs.google.com/leaf?id=0B6n7iMc2P-yQMWViNTUzOWUtNTlmNi00MDQ2LTgyZDktMGU4MTc4MTEyZDI3&sort=name&layout=list&num=50">Chromosome21</a></div>
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<a href="https://docs.google.com/leaf?id=0B6n7iMc2P-yQMTcxZmQwMDgtYzUyNi00MmE2LWEzZjMtNzJlYTQzOTgxZjI3&sort=name&layout=list&num=50">Chromosome 6</a></div>
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<a href="https://docs.google.com/leaf?id=0B6n7iMc2P-yQMTRhYTNjMzYtYWVhMy00OGY4LTg1OGMtMGM5YzIwNDVkOTY1&sort=name&layout=list&num=50">Chromosome 7</a></div>
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<a href="https://docs.google.com/leaf?id=0B6n7iMc2P-yQMDk2NTVjNzgtYTNlYy00OWUwLWExZGMtMWNkZjcxYjM3Zjdk&sort=name&layout=list&num=50">Chromosome 17</a></div>
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<a href="https://docs.google.com/leaf?id=0B6n7iMc2P-yQMDc0ODg4MDEtZjI1Mi00MjBhLWE2OTYtZmQ2NWM4MzM1ZWIy&sort=name&layout=list&num=50">Chromosome 16</a></div>
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<a href="https://docs.google.com/leaf?id=0B6n7iMc2P-yQMDQ0ZWUxMjgtYTQ4Yi00ZjkyLTk4MzYtYjllZjlkZDk1NGU4&sort=name&layout=list&num=50">Chromosome 10</a></div>
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<a href="https://docs.google.com/leaf?id=0B6n7iMc2P-yQZTVlYTJmODktOWFkYS00MzJhLTg2ZjMtYzFmMzFkNjZkOTFk&sort=name&layout=list&num=50">Chromosome 22</a></div>
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<a href="https://docs.google.com/leaf?id=0B6n7iMc2P-yQZWZjOGFhMTgtZDkwZC00MzQ5LTlmMWQtZTJmNTRmMDVlNGFk&sort=name&layout=list&num=50">Chromosome 5</a></div>
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With the scope on xMHC (see our previous posting),Of special interest here are, perhaps, haplotype matches on Chromosome 6, which match the pattern of massive extensive sharing of linked SNPs in the region of xMHC - <a href="https://docs.google.com/leaf?id=0B6n7iMc2P-yQMmRmMjcxYjktOTcwMy00NTI1LTllY2MtODU3ZGM0NWFkZDc4&sort=name&layout=list&num=50">Chrom6-cM </a></div>
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<a href="https://docs.google.com/leaf?id=0B6n7iMc2P-yQOTIyMTI3YjQtYWJhOS00NWQ2LTllM2EtYWI2ZGQyMTNhYjA0&sort=name&layout=list&num=50"></a></div>
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<br /></div>Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com5tag:blogger.com,1999:blog-7120134997435393696.post-10441414837083304322011-12-27T15:19:00.000-08:002011-12-27T15:27:47.369-08:00Experimental test: inferring HLA (haplo)types from DNA nucleotide sequences using HLA*IMP framework<div dir="ltr" style="text-align: left;" trbidi="on">
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjbY05wH5lKepWi5NJ051Q4TthFHj__SLy43l5bWYyqn4C-JYWCsi1qRHQvglcKja53OAmHXbOVV8aAEgL75JxHnfZsL68UYZOxvQqwn7zZttjt0reE8prD-FGcxi22e6RWGE6XtyJGM5Q/s1600/index.jpeg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="177" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjbY05wH5lKepWi5NJ051Q4TthFHj__SLy43l5bWYyqn4C-JYWCsi1qRHQvglcKja53OAmHXbOVV8aAEgL75JxHnfZsL68UYZOxvQqwn7zZttjt0reE8prD-FGcxi22e6RWGE6XtyJGM5Q/s320/index.jpeg" width="320" /></a></div>
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Molecular differences between HLA alleles vary up to 57 nucleotides
within the peptide binding coding region of human Major
Histocompatibility Complex (MHC) genes, but it is still unclear whether
this variation results from a stochastic process or from selective
constraints related to functional differences among HLA molecules.
Although HLA alleles are generally treated as equidistant molecular
units in population genetic studies, DNA sequence diversity among
populations is also crucial to interpret the observed HLA polymorphism (<span class="citation_author">Buhler
S,
</span>
<span class="citation_author">Sanchez-Mazas
A,
</span>
<span class="citation_date">2011</span>
<span class="citation_article_title">HLA DNA Sequence Variation among Human Populations: Molecular Signatures of Demographic and Selective Events.</span>
<span class="citation_journal_title">PLoS ONE</span><span class="citation_issue"> 6(2):</span>
<span class="citation_start_page">e14643.</span>
<span class="citation_doi">doi:10.1371/journal.pone.0014643</span>).</div>
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<span class="st">Traditionally, </span>serology has been used for HLA typing for many decades; however, serological typing of histocompatibility class II molecules depends on the adequate expression of these molecules on the surface of B lymphocytes, the availability of viable cells and a complete set of antisera. However, the application of molecular methods (RFLP, PCR, SSO etc.) to HLA typing has led to the situation whereby nearly every laboratory performs some DNA typing for the detection of HLA alleles.</div>
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<b>Why HLA loci are so important?</b></div>
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<b> <u>HLA loci present the highest degree of polymorphism of all human genetic
systems</u></b>. Prior knowledge of the extent of diversity is essential in the
development and selection of molecular typing methods. Reliable allele
frequencies are also important in allogeneic unrelated hematopoietic
stem cell transplantation to determine the likelihood of finding
closely HLA matched donors for each patient.The genetic diversity of the HLA loci is responsible for the efficiency
of the immune system in eliminating cells carrying foreign antigens.
There is a need to develop a measure of this genetic diversity in order
to assess how different populations are equipped to respond to
foreign-antigen exposure, and to evaluate the contribution of each HLA
locus.</div>
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The HLA system has been extensively studied from an evolutionary
perspective. The region contains a number of closely linked genes whose
products control a variety of functions concerned with the regulation
of immune responses. In addition, the genetic predisposition to over 40
diseases maps to this region. <b>A number of observations indicate that
strong selection is acting on the HLA region, including its extensive
polymorphism with very even allele frequencies, the preferential
occurrence of high levels of variability at positions critical to
antigen recognition, the great age of alleles and the patterns of
linkage disequilibrium among loci. </b>The form of the selection is
unknown. Although balancing selection is a strong candidate, it seems
unlikely that only one selective mechanism is operating in this complex
multigene family region. Mutation, recombination and gene conversion
all contribute to the generation of HLA variability. The apparent great
age of many HLA alleles revealed by phylogenetic analysis suggests that
the absolute rate of production of new variants is not high. Detailed
studies of population and evolutionary features of the HLA region are
necessary for an informed discussion of the evolution of disease
predisposing genes and epitopes, and of complex multigene families (Thomson G.HLA population genetics.1991 Jun;5(2):247-60.)</div>
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</div>
<b>Nomenclature of HLA Alleles</b><br />
<br />
Each HLA allele name has a unique number corresponding to up to four sets of digits separated by colons. The length of the allele designation is dependant on the sequence of the allele and that of its nearest relative. All alleles receive at least a four digit name, which corresponds to the first two sets of digits, longer names are only assigned when necessary.The digits before the first colon describe the type, which often corresponds to the serological antigen carried by an allotype. The next set of digits are used to list the subtypes, numbers being assigned in the order in which DNA sequences have been determined. Alleles whose numbers differ in the two sets of digits must differ in one or more nucleotide substitutions that change the amino acid sequence of the encoded protein. Alleles that differ only by synonymous nucleotide substitutions (also called silent or non-coding substitutions) within the coding sequence are distinguished by the use of the third set of digits. Alleles that only differ by sequence polymorphisms in the introns or in the 5' or 3' untranslated regions that flank the exons and introns are distinguished by the use of the fourth set of digits (further information: <a href="http://hla.alleles.org/nomenclature/naming.html">http://hla.alleles.org/nomenclature/naming.html</a>).<br />
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<a href="http://hla.alleles.org/inc/images/naming.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="192" src="http://hla.alleles.org/inc/images/naming.png" width="320" /></a></div>
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<b>Example </b><br />
<br />
<b>HLA-A</b> identifies HLA A locus<br />
<b>HLA-A1</b> serologically defined antigen<br />
<b>HLA-A*</b> asterisk denotes HLA alleles defined by molecular methods<br />
<b>HLA-A*01 </b>2 digit resolution denotes a group of alleles corresponds usually to serological group – low resolution<br />
<b>HLA-A*0101</b> 4 digit resolution – sequence variation between alleles results in amino acid substitutions<br />
<b>HLA-A010101</b> 6 digit resolution – non coding variation: sequence changes synonymous no amino acid substitution<br />
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<b>HLA types and linked SNPs</b><br />
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<u><b> </b></u><u><b>Still, classical HLA alleles (e.g. HLA-, HLA-B, etc.) are tricky to analyze
with chip technology employed in popular commercial personal genomic
services (23andme, FTDNA's Family Finder and deCODEme)</b></u> , because <span class="st">analysis is a complex process, requiring a large number of multiplex PCR reactions to obtain a patient's full <i>genotype</i>. That is why </span> classical HLA typing methods are often imparctical
for large-scale studies. </div>
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Fortunately for us , Wellcome Trust Centre for Human Genetics described a method for imputing classical alleles from linked SNP genotype data, implemented in the imputation framework (HLA*IMP) (<i>Alexander Dilthey, Loukas Moutsianas, Stephen Leslie, and Gil McVean. HLA*IMP – an integrated framework for imputing classical HLA alleles from SNP genotypes Bioinformatics btr061 first published online February 7, 2011 doi:10.1093/bioinformatics/btr061</i>).</div>
<br />
HLA*IMP imputes HLA type information based on SNP genotype, using methods of iterative model building to select a set of informative SNPs
for particular supported genotyping chips (<b>AffyMetrix 500K, AffyMetrix 900K, Illumina 300K, Illumina 550K,Illumina 650K, Illumina 1M</b>). Thus, HLA*IMP enables researchers to perform classical HLA allele imputation from genotype data collected from several available genome-wide SNP sets through reference to a reference data set of over 2,500 samples of European ancestry with dense SNP data and classical HLA allele types. This reference set includes: <br />
<ul style="text-align: left;">
<li><a href="http://www.b58cgene.sgul.ac.uk/">The 1958 Birth Cohort </a> typed both on the Illumina 1.2M and Affymetrix Genome-Wide Human SNP Array 6.0 chips (TheWellcome Trust Case Control Consortium, 2007) - 2420 genotype samples x 7733 SNP in the extended HLA region.</li>
<li>The HapMap CEU samples (The International HapMap Consortium, 2007) and CEPH CEU+ additional samples (de Bakker et al., 2006) - 92 samples x 7733 BC58-overlapping SNPs)</li>
</ul>
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SNP haplotypes for the 1958BC and CEU+ samples were phased using IMPUTE v2 using the trio-phased HapMap samples as a reference dataset. Classically typed HLA genotypes were then phased into SNP haplotypes by using PHASE (Stephens and Scheet, 2005) applying standard settings for multiallelic loci. The combined reference dataset consists of 5024 haplotypes with data on 7733 SNPs in the HLA region. <b>This splits up into 2474 (HLA-A), 3090 (HLA-B), 2022 (HLA-C), 175 (HLA-DQA1), 2629 (HLA-DQB1), 2665 (HLA-DRB1) locus-specific haplotypes which are used for inference.</b></div>
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<b>The experiment with MDLP dataset</b></div>
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<b>Motivation:</b></div>
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As i previously mentioned in my blog (re: Chromosome 6), 23andme's RelativeFinder and AncestryFinder revealed (among my results) a cluster of a
prominent number of HIR-matches (315), positioned in the exactly the
same subregion of HLA-MHC domain on Chr.6 (21Mb-38Mb). This remarkable
group of matches constitutes almost a half of my total AF/RF matches
(315/720 or 43,75%).<br />
<br />
Earlier i suggested that such a
preponderance of HIR-matches to HLA region is indicative of case of
sharing the same extended HLA haplotype<b>. Until recently, my suggestion rested solely on my intiution. </b>Then, i found solution to HLA*IMP challenges and so far, i've managed to
make HLA*IMP work with 23andme genotyper (Illumina Omnio Express) call
raw data.
</div>
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For my test, i needed to make sure that my data meets the following requirements:</div>
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<ul style="text-align: left;">
<li><b>SNPs must be from the xMHC region (chromosome 6) </b></li>
<li><b>European ancestry of the typed individuals </b></li>
<li><b>sufficient quality and typed SNP density in the HLA region to enable reliable phasing</b></li>
<li><b>since HLA*IMP doesn't provide a direct support for 23andme's chips and i was using the combined set of genotypes from 23andme's chipset v2 and chipset v3, i've choosed "a downgraded" version of Illumina genotyping platform (Illumina 300K)</b></li>
</ul>
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In order to my initial assumption of HLA haplotype sharing i selected 7 participants from my project (including 4 individuals without HIR-sharing on Chromosome 6 (not detected by 23andme's AF) me, my mother and an individual, who has a HIR-match with me and my mother in xMHC region). I converted 23andme's raw data of the project's participants into Plink format, merged the files into one dataset and extracted SNPs on Chromosome 6 using Plink command --chr 6. After that, i converted the genotype data from Plink format to HLA*IMP input data format. As a next step, i carried out quality control on the genotype data, removing SNPs and individuals with too much missing data and aligning complementary SNPs to the HapMap reference strand. Finally, i phased included genotypes to obtain haplotype data. Note: each individual was anonymized by substituting project's ID with prefix N.</div>
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The haplotype data was uploaded to <a href="https://oxfordhla.well.ox.ac.uk/hla/">HLA*IMP back-end web service </a> for imputing HLA types.</div>
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The imputed HLA types look as follows (each individual is represented by 2 HLA haplotypes in HLA-A:HLA-B:HLA-C:HLA-DQA:HLA-DQB:HLA-DRB format)</div>
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</div>
<table border="0" cellpadding="0" cellspacing="0" style="border-collapse: collapse; width: 463px;"><col style="width: 62pt;" width="82"></col>
<col style="width: 68pt;" width="90"></col>
<col style="width: 30pt;" width="40"></col>
<col span="2" style="width: 29pt;" width="39"></col>
<col style="width: 44pt;" width="59"></col>
<col style="width: 44pt;" width="58"></col>
<col style="width: 42pt;" width="56"></col>
<tbody>
<tr height="20" style="height: 15pt;">
<td height="20" style="height: 15pt; width: 62pt;" width="82"><b><a href="http://www.blogger.com/blogger.g?blogID=7120134997435393696" name="RANGE!A1:C15">IndividualID</a></b></td>
<td style="width: 68pt;" width="90"><b>Chromosome</b></td>
<td style="width: 30pt;" width="40"><b>HLAA</b></td>
<td style="width: 29pt;" width="39"><b><a href="http://www.blogger.com/blogger.g?blogID=7120134997435393696" name="RANGE!D1:D15">HLAB</a></b></td>
<td style="width: 29pt;" width="39"><b><a href="http://www.blogger.com/blogger.g?blogID=7120134997435393696" name="RANGE!E1:E15">HLAC</a></b></td>
<td style="width: 44pt;" width="59"><b><a href="http://www.blogger.com/blogger.g?blogID=7120134997435393696" name="RANGE!F1:F15">HLADQA</a></b></td>
<td style="width: 44pt;" width="58"><b><a href="http://www.blogger.com/blogger.g?blogID=7120134997435393696" name="RANGE!G1:G15">HLADQB</a></b></td>
<td style="width: 42pt;" width="56"><b><a href="http://www.blogger.com/blogger.g?blogID=7120134997435393696" name="RANGE!H1:H15">HLADRB</a></b></td>
</tr>
<tr height="20" style="height: 15pt;">
<td height="20" style="height: 15pt;">N1</td>
<td align="right">1</td>
<td align="right" style="color: #38761d;"><b>101</b></td>
<td align="right" style="color: #38761d;"><b>801</b></td>
<td align="right" style="color: #38761d;"><b>701</b></td>
<td align="right" style="color: #38761d;"><b>501</b></td>
<td align="right" style="color: #38761d;"><b>201</b></td>
<td align="right" style="color: #38761d;"><b>301</b></td>
</tr>
<tr height="20" style="height: 15pt;">
<td height="20" style="height: 15pt;">N1</td>
<td align="right">2</td>
<td align="right">2601</td>
<td align="right">2705</td>
<td align="right">102</td>
<td align="right">101</td>
<td align="right">501</td>
<td align="right">101</td>
</tr>
<tr height="20" style="height: 15pt;">
<td height="20" style="height: 15pt;">N6</td>
<td align="right">1</td>
<td align="right">3101</td>
<td align="right">801</td>
<td align="right">701</td>
<td align="right">501</td>
<td align="right">201</td>
<td align="right">301</td>
</tr>
<tr height="20" style="height: 15pt;">
<td height="20" style="height: 15pt;">N6</td>
<td align="right">2</td>
<td align="right">201</td>
<td align="right">1501</td>
<td align="right">304</td>
<td align="right">501</td>
<td align="right">201</td>
<td align="right">301</td>
</tr>
<tr height="20" style="height: 15pt;">
<td height="20" style="height: 15pt;">N3</td>
<td align="right">1</td>
<td align="right">6801</td>
<td align="right">1501</td>
<td align="right">102</td>
<td align="right">101</td>
<td align="right">501</td>
<td align="right">101</td>
</tr>
<tr height="20" style="height: 15pt;">
<td height="20" style="height: 15pt;">N3</td>
<td align="right">2</td>
<td align="right">2301</td>
<td align="right">5201</td>
<td align="right">501</td>
<td align="right">101</td>
<td align="right">501</td>
<td align="right">101</td>
</tr>
<tr height="20" style="height: 15pt;">
<td height="20" style="height: 15pt;">N2</td>
<td align="right">1</td>
<td align="right" style="color: #38761d;"><b>101</b></td>
<td align="right" style="color: #38761d;"><b>801</b></td>
<td align="right" style="color: #38761d;"><b>701</b></td>
<td align="right" style="color: #38761d;"><b>501</b></td>
<td align="right" style="color: #38761d;"><b>201</b></td>
<td align="right" style="color: #38761d;"><b>301</b></td>
</tr>
<tr height="20" style="height: 15pt;">
<td height="20" style="height: 15pt;">N2</td>
<td align="right">2</td>
<td align="right">2601</td>
<td align="right">3801</td>
<td align="right">1203</td>
<td align="right">102</td>
<td align="right">602</td>
<td align="right">1501</td>
</tr>
<tr height="20" style="height: 15pt;">
<td height="20" style="height: 15pt;">N5</td>
<td align="right">1</td>
<td align="right">301</td>
<td align="right">1501</td>
<td align="right">304</td>
<td align="right">501</td>
<td align="right">302</td>
<td align="right">401</td>
</tr>
<tr height="20" style="height: 15pt;">
<td height="20" style="height: 15pt;">N5</td>
<td align="right">2</td>
<td align="right">205</td>
<td align="right">5001</td>
<td align="right">602</td>
<td align="right">501</td>
<td align="right">202</td>
<td align="right">701</td>
</tr>
<tr height="20" style="height: 15pt;">
<td height="20" style="height: 15pt;">N7</td>
<td align="right">1</td>
<td align="right" style="color: #38761d;"><b>101</b></td>
<td align="right" style="color: #38761d;"><b>801</b></td>
<td align="right" style="color: #38761d;"><b>701</b></td>
<td align="right" style="color: #38761d;"><b>501</b></td>
<td align="right" style="color: #38761d;"><b>301</b></td>
<td align="right" style="color: #38761d;"><b>1101</b></td>
</tr>
<tr height="20" style="height: 15pt;">
<td height="20" style="height: 15pt;">N7</td>
<td align="right">2</td>
<td align="right">101</td>
<td align="right">1501</td>
<td align="right">303</td>
<td align="right">103</td>
<td align="right">604</td>
<td align="right">1301</td>
</tr>
<tr height="20" style="height: 15pt;">
<td height="20" style="height: 15pt;">N4</td>
<td align="right">1</td>
<td align="right">301</td>
<td align="right">702</td>
<td align="right">702</td>
<td align="right">401</td>
<td align="right">402</td>
<td align="right">801</td>
</tr>
<tr height="20" style="height: 15pt;">
<td height="20" style="height: 15pt;">N4</td>
<td align="right">2</td>
<td align="right">2402</td>
<td align="right">4002</td>
<td align="right">202</td>
<td align="right">501</td>
<td align="right">301</td>
<td align="right">1101</td><td align="right"></td><td align="right"></td>
</tr>
</tbody></table>
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<div style="text-align: justify;">
The haplotypes should be read as follows (for example, in case of N1): HLA A<span style="color: purple;">*0101</span> : Cw<span style="color: green;">*0701</span> : B<span style="color: magenta;">*0801</span> : DRB1<span style="color: brown;">*0301</span> : DQA1<span style="color: darkorchid;">*0501</span> : DQB1<span style="color: darkgreen;">*0201. </span></div>
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<div style="text-align: justify;">
<span style="color: darkgreen;"><span style="color: black;">From the table posted above, one can easily mention a matching pattern between N1, N2 and N7, as they share the similiar haplotype. As a matter of fact N1 (ny mother), N2 (me) and N7 share HIR-segment (matching DNA segment equal to or greater than seven Centimorgans (abbreviated as cMs) on one segment with 700 or more SNPs), found by RelativeFinder service at 23andme.</span></span></div>
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<div style="text-align: justify;">
<span style="color: darkgreen;"><span style="color: black;">Thus, it is safe to conclude that the imputation was accurate and </span></span>my initial suggestion seems to be backed up by HLA imputation</div>
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<b><span style="color: darkgreen;"><span style="color: black;">The practical implications of test</span></span></b></div>
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<span style="color: darkgreen;"><span style="color: black;">Aside</span></span><span style="color: darkgreen;"><span style="color: black;"> from the medical usefulness, there are also some benefits of knowing HLA type for genetic genealogists:</span></span></div>
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<span style="color: darkgreen;"><span style="color: black;"><br /> </span></span></div>
<div style="text-align: justify;">
<span style="color: darkgreen;"><span style="color: black;">1) First of all, it is possible to determine the nature of the sharing the segments in xMHC region on Chromosome 6. Consider the aforementioned extended haplotype </span></span>HLA A<span style="color: purple;">*0101</span> : Cw<span style="color: green;">*0701</span> : B<span style="color: magenta;">*0801</span> : DRB1<span style="color: brown;">*0301</span> : DQA1<span style="color: darkorchid;">*0501</span> : DQB1<span style="color: darkgreen;">*0201<span style="color: black;"> (in shorthand:</span> </span>A1::DQ2<span style="color: darkgreen;">).</span><b>A1::DQ2 haplotype creates a conundrum for the evolutionary study of recombination.A1::DQ2 does not follow the expected dynamics. Other haplotypes exist in the region of Europe where this haplotype formed and expanded, some of these haplotypes also are ancestral and also are quite large. At 4.7 million nucleotides in length and ~300 genes the locus had resisted the effects of recombination, either as a consequence of <u>recombination-obstruction within the DNA, as a consequence of repeated selection for the entire haplotype, or both</u>.
The length of the haplotype is remarkable because of the rapid rate of
evolution at the HLA locus should degrade such long haplotypes.</b> <u><sup class="reference" id="cite_ref-pmid10319267_2-1"><a href="http://en.wikipedia.org/wiki/HLA_A1-B8-DR3-DQ2#cite_note-pmid10319267-2"></a></sup></u><b><u>A1::DQ2 is the most frequent haplotype of its length found in US Caucasians, ~15% carry this common haplotype.</u></b><span style="color: darkgreen;"><span style="color: black;"> The SNP analysis of the haplotype suggests a potential founding affect of 20,000 years within Europe, though conflicts in interpreting this information are now apparent. The last possible point of a constriction forcing climate was the Younger Dryas before 11,500 calendar years ago, and so the haplotype has taken on various forms of the name, Ancestral European Haplotype, lately called Ancestral Haplotype A1-B8 (AH8.1). It is one of 4 that appear common to western Europeans and other Asians. Assuming that the haplotype frequency was 50% at the Younger Dryas and declined by 50% every 500 years the haplotypes should only be present below 0.1% in any European population. Therefore it exceeds the expected frequency for a founding haplotype by almost 100 fold. For genetic genealogist, the said would mean that the hotspot of DNA matching in xMHC region <b>could be </b>indicative of very distant common ancestor, probably as recent as Neolithic era.</span></span></div>
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<div style="text-align: justify;">
<span style="color: darkgreen;"><span style="color: black;">2)</span></span><span style="color: darkgreen;"><span style="color: black;">It is also possible to infer the geographic ditribution of a particular HLA haplotype. Using the same A 1::DQ2 haplotype, we could see that it is found in
<b>Iceland, Pomors of Northern Russia, the Serbians of Northern Slavic
descent, Basque, and areas of Mexico where Basque settled in larger
numbers</b>. The haplotypes <b>great abundance in the most isolated geographic
region of Western Europe, Ireland, in Scandinavians and Swiss</b> suggests
that low abundance in France and Latinized Iberia are the result of
displacements that took place after the Neolithic onset. This implies a
founding presence in Europe that exceeds 8000 years. </span></span></div>
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<span style="color: darkgreen;"><span style="color: black;"><br /></span></span></div>
<div style="text-align: justify;">
<span style="color: darkgreen;"><span style="color: black;"><a href="http://www.allelefrequencies.net/hla6003a.asp">The database of allele frequencies</a> is a very convenient tool for analyzing HLA haplotype frequency in a worldwide scale.</span></span></div>
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<table class="bbc_table"><tbody>
<tr><td>1 </td><td><span class="bbc_color" style="color: black;"><b>A*01:01</b>-<b>B*08:01</b>-<b>C*07:01</b>-<b>DRB1*03:01</b>-<b>DQB1*02:01</b></span> </td><td><img alt="" class="bbc_img" src="http://www.allelefrequencies.net/images/SFlags/IRL.bmp" /></td><td><a class="bbc_link new_win" href="http://www.allelefrequencies.net/pop6001c.asp?pop_id=2275" target="_blank">Ireland South </a></td><td><div style="text-align: right;">
11.50</div>
</td><td><img alt="" class="bbc_img" height="10" src="http://www.allelefrequencies.net/images/bar_10.gif" width="11" /></td><td><div style="text-align: right;">
250</div>
</td><td><div align="center">
<a class="bbc_link new_win" href="http://www.allelefrequencies.net/hla6014a.asp?hla_haplotype=A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01" target="_blank"><img alt="" class="bbc_img" src="http://www.allelefrequencies.net/images/icon_world.gif" /></a> <a class="bbc_link new_win" href="http://www.allelefrequencies.net/hla6014a.asp?hla_haplotype=A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01" target="_blank"><img alt="" class="bbc_img" src="http://www.allelefrequencies.net/images/icon_world.gif" /></a></div>
</td></tr>
<tr><td>2 </td><td><span class="bbc_color" style="color: black;"><b>A*01:01</b>-<b>B*08:01</b>-<b>C*07:01</b>-<b>DRB1*03:01</b>:01-<b>DQB1*02:01</b></span> </td><td><img alt="" class="bbc_img" src="http://www.allelefrequencies.net/images/SFlags/ENG.bmp" /></td><td><a class="bbc_link new_win" href="http://www.allelefrequencies.net/pop6001c.asp?pop_id=2837" target="_blank">England North West </a></td><td><div style="text-align: right;">
9.50</div>
</td><td><img alt="" class="bbc_img" height="10" src="http://www.allelefrequencies.net/images/bar_10.gif" width="9" /></td><td><div style="text-align: right;">
298</div>
</td><td><div align="center">
<a class="bbc_link new_win" href="http://www.allelefrequencies.net/hla6014a.asp?hla_haplotype=A*01:01-B*08:01-C*07:01-DRB1*03:01:01-DQB1*02:01" target="_blank"><img alt="" class="bbc_img" src="http://www.allelefrequencies.net/images/icon_world.gif" /></a> <a class="bbc_link new_win" href="http://www.allelefrequencies.net/hla6014a.asp?hla_haplotype=A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01" target="_blank"><img alt="" class="bbc_img" src="http://www.allelefrequencies.net/images/icon_world.gif" /></a></div>
</td></tr>
<tr><td>3 </td><td><span class="bbc_color" style="color: black;"><b>A*01:01</b>-<b>B*08:01</b>-<b>C*07:01</b>-<b>DRB1*03:01</b>-<b>DQB1*02:01</b>-DPB1*04:01</span> </td><td><img alt="" class="bbc_img" src="http://www.allelefrequencies.net/images/SFlags/IRL.bmp" /></td><td><a class="bbc_link new_win" href="http://www.allelefrequencies.net/pop6001c.asp?pop_id=2275" target="_blank">Ireland South </a></td><td><div style="text-align: right;">
8.30</div>
</td><td><img alt="" class="bbc_img" height="10" src="http://www.allelefrequencies.net/images/bar_10.gif" width="8" /></td><td><div style="text-align: right;">
250</div>
</td><td><div align="center">
<a class="bbc_link new_win" href="http://www.allelefrequencies.net/hla6014a.asp?hla_haplotype=A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*04:01" target="_blank"><img alt="" class="bbc_img" src="http://www.allelefrequencies.net/images/icon_world.gif" /></a> <a class="bbc_link new_win" href="http://www.allelefrequencies.net/hla6014a.asp?hla_haplotype=A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01" target="_blank"><img alt="" class="bbc_img" src="http://www.allelefrequencies.net/images/icon_world.gif" /></a></div>
</td></tr>
<tr><td>4 </td><td><span class="bbc_color" style="color: black;"><b>A*01:01</b>-<b>B*08:01</b>-<b>C*07:01</b>-<b>DRB1*03:01</b>-<b>DQB1*02:01</b></span> </td><td><img alt="" class="bbc_img" src="http://www.allelefrequencies.net/images/SFlags/POL.bmp" /></td><td><a class="bbc_link new_win" href="http://www.allelefrequencies.net/pop6001c.asp?pop_id=2413" target="_blank">Poland </a></td><td><div style="text-align: right;">
4.00</div>
</td><td><img alt="" class="bbc_img" height="10" src="http://www.allelefrequencies.net/images/bar_10.gif" width="4" /></td><td><div style="text-align: right;">
200</div>
</td><td><div align="center">
<a class="bbc_link new_win" href="http://www.allelefrequencies.net/hla6014a.asp?hla_haplotype=A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01" target="_blank"><img alt="" class="bbc_img" src="http://www.allelefrequencies.net/images/icon_world.gif" /></a> <a class="bbc_link new_win" href="http://www.allelefrequencies.net/hla6014a.asp?hla_haplotype=A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01" target="_blank"><img alt="" class="bbc_img" src="http://www.allelefrequencies.net/images/icon_world.gif" /></a></div>
</td></tr>
<tr><td>5 </td><td><span class="bbc_color" style="color: black;"><b>A*01:01</b>-<b>B*08:01</b>-<b>C*07:01</b>-<b>DRB1*03:01</b>-<b>DQB1*02:01</b></span> </td><td><img alt="" class="bbc_img" src="http://www.allelefrequencies.net/images/SFlags/USA.bmp" /></td><td><a class="bbc_link new_win" href="http://www.allelefrequencies.net/pop6001c.asp?pop_id=2421" target="_blank">USA Hispanic pop 2 </a></td><td><div style="text-align: right;">
1.78</div>
</td><td><img alt="" class="bbc_img" height="10" src="http://www.allelefrequencies.net/images/bar_10.gif" width="1" /></td><td><div style="text-align: right;">
1,999</div>
</td><td><div align="center">
<a class="bbc_link new_win" href="http://www.allelefrequencies.net/hla6014a.asp?hla_haplotype=A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01" target="_blank"><img alt="" class="bbc_img" src="http://www.allelefrequencies.net/images/icon_world.gif" /></a> <a class="bbc_link new_win" href="http://www.allelefrequencies.net/hla6014a.asp?hla_haplotype=A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01" target="_blank"><img alt="" class="bbc_img" src="http://www.allelefrequencies.net/images/icon_world.gif" /></a></div>
</td></tr>
<tr><td>6 </td><td><span class="bbc_color" style="color: black;"><b>A*01:01</b>-<b>B*08:01</b>-<b>C*07:01</b>-<b>DRB1*03:01</b>-<b>DQB1*02:01</b>-DPB1*01:01</span> </td><td><img alt="" class="bbc_img" src="http://www.allelefrequencies.net/images/SFlags/IRL.bmp" /></td><td><a class="bbc_link new_win" href="http://www.allelefrequencies.net/pop6001c.asp?pop_id=2275" target="_blank">Ireland South </a></td><td><div style="text-align: right;">
1.40</div>
</td><td><img alt="" class="bbc_img" height="10" src="http://www.allelefrequencies.net/images/bar_10.gif" width="1" /></td><td><div style="text-align: right;">
250</div>
</td><td><div align="center">
<a class="bbc_link new_win" href="http://www.allelefrequencies.net/hla6014a.asp?hla_haplotype=A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*01:01" target="_blank"><img alt="" class="bbc_img" src="http://www.allelefrequencies.net/images/icon_world.gif" /></a> <a class="bbc_link new_win" href="http://www.allelefrequencies.net/hla6014a.asp?hla_haplotype=A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01" target="_blank"><img alt="" class="bbc_img" src="http://www.allelefrequencies.net/images/icon_world.gif" /></a></div>
</td></tr>
<tr><td>7 </td><td><span class="bbc_color" style="color: black;"><b>A*01:01</b>-<b>B*08:01</b>-<b>C*07:01</b>-<b>DRB1*03:01</b>-<b>DQB1*02:01</b></span> </td><td><img alt="" class="bbc_img" src="http://www.allelefrequencies.net/images/SFlags/USA.bmp" /></td><td><a class="bbc_link new_win" href="http://www.allelefrequencies.net/pop6001c.asp?pop_id=2419" target="_blank">USA African American pop 4 </a></td><td><div style="text-align: right;">
1.39</div>
</td><td><img alt="" class="bbc_img" height="10" src="http://www.allelefrequencies.net/images/bar_10.gif" width="1" /></td><td><div style="text-align: right;">
2,411</div>
</td><td><div align="center">
<a class="bbc_link new_win" href="http://www.allelefrequencies.net/hla6014a.asp?hla_haplotype=A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01" target="_blank"><img alt="" class="bbc_img" src="http://www.allelefrequencies.net/images/icon_world.gif" /></a> <a class="bbc_link new_win" href="http://www.allelefrequencies.net/hla6014a.asp?hla_haplotype=A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01" target="_blank"><img alt="" class="bbc_img" src="http://www.allelefrequencies.net/images/icon_world.gif" /></a></div>
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<tr><td>8 </td><td><span class="bbc_color" style="color: black;"><b>A*01:01</b>-<b>B*08:01</b>-<b>C*07:01</b>-<b>DRB1*03:01</b>-<b>DQB1*02:01</b></span> </td><td><img alt="" class="bbc_img" src="http://www.allelefrequencies.net/images/SFlags/USA.bmp" /></td><td><a class="bbc_link new_win" href="http://www.allelefrequencies.net/pop6001c.asp?pop_id=2420" target="_blank">USA Asian pop 2 </a></td><td><div style="text-align: right;">
0.09</div>
</td><td><img alt="" class="bbc_img" height="10" src="http://www.allelefrequencies.net/images/bar_10.gif" width="0" /></td><td><div style="text-align: right;">
1,772</div>
</td><td><div align="center">
<a class="bbc_link new_win" href="http://www.allelefrequencies.net/hla6014a.asp?hla_haplotype=A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01" target="_blank"><img alt="" class="bbc_img" src="http://www.allelefrequencies.net/images/icon_world.gif" /></a> </div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhH_mKnxpltLbFyeoy-fRVDEt9wuEARDcii4qIGR9xWCzYly3pGigxEwuQ2J1rpbNy52wdYYnaFI3S5NYQwlGF-rRWX4gARq2Zo7EnfNSMIWrayE6ff43M3upj7AYGpThi91cEUSV4PpSY/s1600/index.jpeg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="177" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhH_mKnxpltLbFyeoy-fRVDEt9wuEARDcii4qIGR9xWCzYly3pGigxEwuQ2J1rpbNy52wdYYnaFI3S5NYQwlGF-rRWX4gARq2Zo7EnfNSMIWrayE6ff43M3upj7AYGpThi91cEUSV4PpSY/s320/index.jpeg" width="320" /></a></div>
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<br /></div>Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com3tag:blogger.com,1999:blog-7120134997435393696.post-13384357599012935112011-12-06T02:26:00.001-08:002011-12-06T09:44:51.590-08:00Experimental test: running Admixture on phased samples and estimating ancestries at each locus in a population of admixed individuals (LAMP))<div dir="ltr" style="text-align: left;" trbidi="on">
As a methodological tool, there is nothing wrong with the combined usage of Plink/Admixture/Lamp for assessing the popupaltion stratification and the levels of individual admixtures. One of the goals of our project is to expose both the advantages and the limitation of particular methodologies in BGA analyses, and therefore this particular experimental test seeks to expose the grip of unified Plink/Admixture/Lamp approaches as a methodological contrivance.<br />
Thus the goal of the experiment described herein is to lay bare some of practical and thereoretical obstacles that have hitherto obscured the legibility of our previous biogenographic analysis of the population substructures in Europe.<br />
<br />
<div style="text-align: justify;">
We routinely began our analysis in Plink software to filter the combined dataset to include only SNPs on the 22 autosomal chromosomes with minor allele frequency >1% and genotyping success >99%. </div>
<div style="text-align: justify;">
Because background linkage disequilibrium (LD) can affect both principal component and structure-like analysis, wethinned the marker set by excluding SNPs in strong LD (pairwise genotypic correlation r2>0.4) in a window of 100 SNPs (sliding the window by 10 SNPs at a time). We also used the following Plink techniques for obtaining the homogeneous sample: pairwise clustering based on IBS
is for detecting pairs of individuals who look more different from each other than
you'd expect in a random, homogeneous sample; evaluating </div>
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Those reference individials, who look more different (more than 3 SD) to the rest of the data set and/or have high <tt>PIHAT</tt> values ( greater than
0.05) and higher degree of inbreeding (homozygocity)* were removed from our training set.</div>
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-</div>
<div style="text-align: justify;">
* Note that the degree of inbreeding is defined as the probability that identical homozygocity occurs in a locus. </div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhpaR56BzpKWvhuV8opRFOpJgqZxIoAhE2Uz5VQos01cp474dapQJpt-F-LdUDHLD6XsBzVthgvg02E1wYreBC_S3G3zZBt4ws9TaKdyuy-_og8v52yAN-eUDr5kdu6sxWa6KjHL8_q7tQ/s1600/homozyg.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="443" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhpaR56BzpKWvhuV8opRFOpJgqZxIoAhE2Uz5VQos01cp474dapQJpt-F-LdUDHLD6XsBzVthgvg02E1wYreBC_S3G3zZBt4ws9TaKdyuy-_og8v52yAN-eUDr5kdu6sxWa6KjHL8_q7tQ/s640/homozyg.jpg" width="640" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;"><b>The stratification of samples according to the levels of homozygocity,X axis -total ammount of homozygous segments in Kb (kilobases) units; Y-axis - average size of homozygous segments in Kb units </b></td><td class="tr-caption" style="text-align: center;"><br /></td><td class="tr-caption" style="text-align: center;"><br /></td><td class="tr-caption" style="text-align: center;"></td></tr>
</tbody></table>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhmClnZTLsQcVzfCXSqW1T7WnHWCRnx89xU2ka6BiwfZUwDZO5m7BMJLLWgabYgigd-kagGzRNyq-V6BdXgsSRiS35rvQSm-ZRc9We5nY2fwxq-phMCleJZPyuWBjC3HtApzBY4rb1lZHY/s1600/homozyg2.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="449" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhmClnZTLsQcVzfCXSqW1T7WnHWCRnx89xU2ka6BiwfZUwDZO5m7BMJLLWgabYgigd-kagGzRNyq-V6BdXgsSRiS35rvQSm-ZRc9We5nY2fwxq-phMCleJZPyuWBjC3HtApzBY4rb1lZHY/s640/homozyg2.jpg" width="640" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;"><b>The levels of individual homozygocity in data set: NSEG (number of segments) on X axis is plotted against the total length of homozygous segments in KB (Y axis) </b></td><td class="tr-caption" style="text-align: center;"><br /></td></tr>
</tbody></table>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEinQqZqGHfvrOW2Wy9BFO9DMIbFmp94KYswaISWWeZaxyjZKvMMWrZz7eYkUj9TGHciu0jLpQ-Lmm5Ewa418zNefP87vQCrV5zfV4aiOr0p9VZXO0-2h7jdfZ8OVVffSbEHIaY0kA-XuQ0/s1600/IBD+clustering.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="454" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEinQqZqGHfvrOW2Wy9BFO9DMIbFmp94KYswaISWWeZaxyjZKvMMWrZz7eYkUj9TGHciu0jLpQ-Lmm5Ewa418zNefP87vQCrV5zfV4aiOr0p9VZXO0-2h7jdfZ8OVVffSbEHIaY0kA-XuQ0/s640/IBD+clustering.jpg" width="640" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">The pairwise clustering based on IBD. The total length of IBD segments (X axis) is plotted against PIHAT values (<br />
<pre>P(IBD=2)+0.5*P(IBD=1) ( proportion IBD ))</pre>
</td></tr>
</tbody></table>
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<br />
<br />
After frequency and genotyping pruning, and removing the outliers, the final data set consisted of 90455 SNPs and 317 individuals (289 males, 82 females) that were used in subsequent analyses.<br />
<br />
First of all, we used ADMIXTURE (Alexander, Novembre, Lange 2009) implementing a structure-like<br />
(Pritchard, Stephens, Donnelly 2000) model-based maximum likelihood (ML) clustering algorithm to assess population structure <b>in the whole data set </b>.<br />
<br />
In order to maintain the compatibility with <a href="http://magnusducatus.blogspot.com/2011/08/i-have-modified-diydodecad-calculator.html">MDLP calculator</a>, we choosed K=7 as a sensible modeling choice. The Q estimates, obtained from Admixture run, were plotted in R.<br />
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<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhf_3p2HL6JpMUaIB8GWrS9u6XNnFKncI_9jbSaNug-1ThKPKARRdNFSldMVnUH5nKEPP45TWjKe8z9qO_wCzLGpsgppezQ9gx3KCaSSzGK8LIt-s1PWtZrI5lha1qRjxDu_1Vr9Vs6tjM/s1600/MDLPV4.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="640" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhf_3p2HL6JpMUaIB8GWrS9u6XNnFKncI_9jbSaNug-1ThKPKARRdNFSldMVnUH5nKEPP45TWjKe8z9qO_wCzLGpsgppezQ9gx3KCaSSzGK8LIt-s1PWtZrI5lha1qRjxDu_1Vr9Vs6tjM/s640/MDLPV4.png" width="329" /></a></div>
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Please note that only participants of the MDLP project are plotted on this barplot. The full list of Q estimates (including "<b>reference" populations</b>) is available in <a href="https://docs.google.com/spreadsheet/ccc?key=0Aqn7iMc2P-yQdEtVMG45QVVnbnM1TEVDbF90TGMyM1E&hl=en_US#gid=0"><b>this spreadsheet</b></a>.<br />
<br />
The seven ancestral components (K) inferred at this level of resolution are:<br />
<br />
<b style="color: red;">Trans-Caucasian -red</b><b><span style="color: yellow;"> </span></b><br />
<b><span style="color: yellow;">Balkanic/Mediterrean -yellow </span></b><b> </b><br />
<b><span style="color: lime;">North-Caucasian -green</span></b><br />
<b><span style="color: lime;"></span></b><b><span style="color: cyan;">West-European </span> </b><br />
<b><span style="color: #3d85c6;">Altaic </span></b><span style="color: #3d85c6;">- light blue</span><br />
<b style="color: #073763;">Balto-Slavic </b><span style="color: #073763;">- dark blue</span><b style="color: #741b47;"> </b><br />
<b style="color: #741b47;">Balto-Finnic/North-European -purple</b><br />
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As usual, we labeled these components for <b>mnemonic purposes only: researchers should thus be cautious in interpreting the inferred components in terms of conventional population history.</b><br />
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgaMedR7ZSRzeqQVgUOWqW8X84-E7BLYnP2rzlj9VSpP0hnOl5sB3KFo6aESNAFVfYEuVuggLQk7ihdiLe38gtoQfxw_59WO4X21ISpgWDdSDtKuSVFIsyKJ6k928ZsdPeWIdALOq42_MA/s1600/MDLP+v4+components.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="400" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgaMedR7ZSRzeqQVgUOWqW8X84-E7BLYnP2rzlj9VSpP0hnOl5sB3KFo6aESNAFVfYEuVuggLQk7ihdiLe38gtoQfxw_59WO4X21ISpgWDdSDtKuSVFIsyKJ6k928ZsdPeWIdALOq42_MA/s400/MDLP+v4+components.jpg" width="332" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;"><b>A neighbor-joining tree based on inter-population Fst distances</b></td><td class="tr-caption" style="text-align: center;"></td><td class="tr-caption" style="text-align: center;"></td></tr>
</tbody></table>
<b> </b>As a next step we splitted whole-genome PLINK binary files (371 samples) to 22 separate chromosomal chunks and sunsequently used Admixture software to evaluate population structure <b>on each of 22 chromosomes.</b> After that we used <a href="http://www.cs.columbia.edu/%7Egusev/germline/">a pipeline for phasing PLINK format data with BEAGLE and converting phased datat back to PLINK format.</a><br />
<br />
We assumed that the admixed population (represented by V<i>ID</i> samples) being analyzed in our project has arisen from the
admixture of 7 separate ancestral populations, and that phased data are
available from unadmixed reference populations are closely related
to the true ancestral population. Under this assumption we again used ADMIXTURE software to infer ancestral components <b>in the phased data set of separate chromosomes. Please note that we intentionally left those components unlabeled.</b><br />
<br />
<div style="text-align: justify;">
Finally, we used LAMP (Local Ancestry in adMixed Populations) (Sankararaman et al.2008) for inferring individual admixture. This simply involves the application of either of the above procedures (locus-specific ancestries when the ancestral populations are not known or locus-specific ancestries of the ancestral populations are known) followed by averaging these locus-specific ancestries to obtain the individual admixture. We estimated allele frequencies (stratified by
a categorical cluster) in Plink software (to produce summary of allele frequencies that is stratified by
a categorical cluster variable, we used the plink --file data --freq <b><tt>--within</tt></b>
option).We fixed the HapMap recombination rate (estimated separately for each of 22 chromosomes) according to the units of distance specified in chromosome posfile. We also used different number of generations G (generations) 5, 10,25 , assuming that there are <i>K</i>=7 ancestral populations <i>A</i><sub>1</sub>, …, <i>A<sub>K</sub></i> that have been mixing for <b><i>g</i>=5,10,25</b> generations. The ancestries generated by LAMP were visualized in Generategraph package.</div>
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We organized the output into separate Excel spreadsheets <span class="st">to help<i> </i></span><span class="st">facilitate analysis </span><span class="st">and interpretation of the results. Each of provided Excel spreadsheets includes the following sections:</span></div>
<div style="text-align: justify;">
<span class="st"><br /></span></div>
<div style="text-align: justify;">
<span class="st">1) ADMIXTURE output for unphased chromosomal data (<b>Chr*-phased</b>)</span></div>
<div style="text-align: justify;">
<span class="st">2) ADMIXTURE output for unphased </span><span class="st">chromosomal data (<b>Chr*-unphased</b>)</span></div>
<div style="text-align: justify;">
<span class="st">3) LAMP results for G=5 (<b>Chr*-lamp-gen5</b>)</span></div>
<div style="text-align: justify;">
<span class="st">4) LAMP results for G=10 (<b>Chr*-lamp-gen5</b>)</span></div>
<div style="text-align: justify;">
<span class="st">5) LAMP results for G=25 (<b>Chr*-lamp-gen5</b>)</span><span class="st"> </span> </div>
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Links<br />
<br />
<a href="https://docs.google.com/spreadsheet/ccc?key=0Aqn7iMc2P-yQdEY2bno5RERlaXFSUmpoZDdjUUlZZEE">Chr1</a> <a href="https://docs.google.com/spreadsheet/ccc?key=0Aqn7iMc2P-yQdGJCUzJOSVdsM3dsMFVacDdUVHFMSVE">Chr2</a> <a href="https://docs.google.com/spreadsheet/ccc?key=0Aqn7iMc2P-yQdGNjQlJ6MDdRNFRtRFh1MG1rb01xdVE">Chr3 </a><a href="https://docs.google.com/spreadsheet/ccc?key=0Aqn7iMc2P-yQdENkV3p3UHBBd2pwcjlwcXo4Q0tiZWc">Chr4</a> <a href="https://docs.google.com/spreadsheet/ccc?key=0Aqn7iMc2P-yQdFJkZG9ZWEJSSWtXam5fdHJqY1JURGc">Chr5</a> <a href="https://docs.google.com/spreadsheet/ccc?key=0Aqn7iMc2P-yQdFZOR0p5bHdXRG44bjVVaEdlVktHTmc">Chr6 </a><a href="https://docs.google.com/spreadsheet/ccc?key=0Aqn7iMc2P-yQdHRYNHg3bXp2bXpKVF9oQWxVNC1wVGc">Chr7</a> <a href="https://docs.google.com/spreadsheet/ccc?key=0Aqn7iMc2P-yQdGxIU0JjM0trNFdPZlRKWk9uMno3X0E">Chr8</a><br />
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The rest of chromosomal data will be added <i>asap</i>. </div>
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<b> </b> <b> </b><br />
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<br /></div>Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com0tag:blogger.com,1999:blog-7120134997435393696.post-25091361523558682862011-11-14T16:21:00.001-08:002011-11-15T05:37:58.220-08:00Some achievements of the MDL project<div dir="ltr" style="text-align: left;" trbidi="on">
Looking back at the<a href="http://magnusducatus.blogspot.com/2011_04_17_archive.html"> project's goals posited 6 months ago,</a> we would like to recapitulate some of the most important goals in order to analyzes how they have been achieved:<br />
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1<i>.Performing the comprehensive Plink analysis, including the estimation of homozygous ROH (shared clusters and groups of homozygosity), possible Mendelian errors, extended LD-haplotypes (based on values of R2), shared IBD segments and IBS matrix (Plink format).</i><br />
<br />
Although we performed all described types of Plink analysises and eve shared some results on the project's blog, we didn't consider these results worth of extensive coverage. And likewise, there was no interest in those analysises on behalf of the project's members.<br />
<br />
<a href="http://magnusducatus.blogspot.com/2011/04/experiments-with-relatedness.html">Experiments with relatedness</a><br />
<a href="http://magnusducatus.blogspot.com/2011/05/grapho-analytical-approach-to.htmls">Graphoanalytical approach to visualizing relatedness</a><br />
<a href="http://magnusducatus.blogspot.com/2011/05/ibd-sharing.html">IBD sharing </a><br />
<a href="http://magnusducatus.blogspot.com/2011/05/ibs-similarity-matrix-in-r.html">IBS similarity matrix in R </a><br />
<br />
2.<i>Phasing the genotype files, i.e establishing the haploid phase (this is a separate analysis demanding genotypes of your parents, so it will not be performed on a regular base) (Beagle or Merlin output format). </i><br />
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We<i> </i>performed <i>ad-hoc</i> phasing of the genotypes in our project (MDLP) and, in order to assess possible discrepancies between phased and unphased data, we
performed ADMIXTURE analysis (with 4 assumed clusters K=4) separately
for original unphased dataset and BEAGLE-phased dataset.<br />
<br />
<a href="http://magnusducatus.blogspot.com/2011/10/analyzing-admixture-in-phased-vunphased.html">Analyzing admixture in phased v.unphased dataset</a><br />
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3. <i>Using AISconvert (based on HIRsearch) and Germline software to detect IBD segments.</i><br />
<br />
Used only occassionally in combination with other analyses<br />
<br />
<a href="http://magnusducatus.blogspot.com/2011/10/analyzing-admixture-in-phased-vunphased.html">Analyzing admixture in phased v.unphased dataset </a><br />
<a href="http://magnusducatus.blogspot.com/2011/05/grapho-analytical-approach-to.html">Grapho-analytical approach to the visualisation of IBD shared segments </a><br />
<a href="http://magnusducatus.blogspot.com/2011/05/ibd-sharing.html">IBD sharing </a><br />
<br />
<br />
4.<i>Using ADMIXTURE/STRUCTURE software for detecting admixture clusters </i>and claculating allele frequencies.<br />
<br />
We performed a plenty of ADMIXTURE and STRUCTURE runs (using different a priori number of assumed clusters under different models of admixture). Discussions of ADMIXTURE results contibuted the most signficant part to the MDLP's blog.<br />
The allele frequencies, estimated in K=7 Admixture run, were provided for creating a custom modification of DIYDodecad's calculator (MDLP).<br />
<br />
<a href="http://magnusducatus.blogspot.com/2011/10/analyzing-admixture-in-phased-vunphased.html">Analyzing admixture in phased v.unphased dataset </a><br />
<a href="http://magnusducatus.blogspot.com/2011/04/first-results-admixture-unsupervised.html">First results: Admixture unsupervised run </a><br />
<a href="http://magnusducatus.blogspot.com/2011/05/admixture-analysis-sorted-after-baltic.html">Admixture analysis: sorted after Baltic-Slavic component </a><br />
<a href="http://magnusducatus.blogspot.com/2011/05/admixture-results-baltic-slavic.html">Admixture results: Baltic-Slavic</a><br />
<a href="http://magnusducatus.blogspot.com/2011/05/admixture-analysis-rest-of-groupings.html">Admixture analysis: the rest of groupings</a><br />
<a href="http://magnusducatus.blogspot.com/2011/05/output-of-plink-and-admixture.html">The output of the PLINK and ADMIXTURE algorithms </a><br />
<a href="http://magnusducatus.blogspot.com/2011/05/admixture-clusters-mclust-and.html">Admixture clusters, Mclust and populations concordance </a><br />
<a href="http://www.blogger.com/blogger.g?blogID=7120134997435393696#editor/target=post;postID=982453850437621557">DIYDodecad calculator v2.0 for my BGA project (MDLP).</a><br />
<a href="http://magnusducatus.blogspot.com/2011/08/mark-jost-has-posted-root-means-square.html">Root Means Square Comparison Excel 2007 Macro Enabled XLSM spreadsheet for the Magnus Ducatus Lithuaniae Project data</a><br />
<br />
and many more .. <br />
<br />
<h3 class="post-title entry-title">
</h3>
5.<i> Creating MDS and PCA plots</i><span style="font-size: x-small;"></span><br />
<a href="http://magnusducatus.blogspot.com/2011/05/pca-plots-eigensoft.html">PCA plots (Eigensoft)</a><br />
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<a href="http://magnusducatus.blogspot.com/2011/06/pca-plots-for-reference-populations-and.html">PCA plots for reference populations and project participants</a><br />
<a href="http://magnusducatus.blogspot.com/2011/08/mds-and-pca-plots-for-v157-v247.html">MDS and PCA plots: for V157-V247</a><br />
<a href="http://magnusducatus.blogspot.com/2011/07/close-up-on-core-of-mdl-project.html">A close-up on "the core" of the MDL project </a><br />
<br />
6.<i>Creating RHHmapper schemes showing the location of rare heterozygous and homozygous genotypes</i><br />
<br />
<a href="http://magnusducatus.blogspot.com/2011/05/rhh-mapper-results-for-v158-v165-and.html">RHH mapper: results for V158-V165 and V201-V202</a><br />
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<span style="font-size: x-small;"> </span></div>Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com0tag:blogger.com,1999:blog-7120134997435393696.post-91220196263977672972011-11-14T13:59:00.001-08:002011-11-14T16:00:43.488-08:007 months of MDLP project: alpha phase is over<div dir="ltr" style="text-align: left;" trbidi="on">
<div style="text-align: justify;">
We would like to announce that the project has been active for more than 6 months, i.e fairly long to accomplish some of the posited goals.
The main goal of the project's preliminary (alpha) phase was to collect a statistically reliable sample for <span class="st">obtaining the <i>statistically significant</i> results.</span>
<span class="st">The current dataset (MDLP v2) includes 531 unrelated individuals (379 males, 152 females) with 310652 SNPs, of those 183 individuals (48 Romanians, 2 Russians,17 Chuvashes,12 Uzbeks,16 Turks,18 Armenians,15 Lezgins,20 Georgians,19 Hungarians,8 Lithuanians,8 Belorussians) from <a href="http://www.nature.com/nature/journal/v466/n7303/full/nature09103.html">Behar et all (2010)</a> dataset.</span><span class="st">41 individuals from <a href="http://www.google.ee/url?sa=t&rct=j&q=hgdp&source=web&cd=2&ved=0CC8QFjAB&url=http%3A%2F%2Fwww.cephb.fr%2Fen%2Fhgdp%2Fdiversity.php%2F&ei=R5vBTrKkKcvZ4QTAhqDKBA&usg=AFQjCNHDf3N1hIPJXj6Kpnd0xUJg0GzM1A&cad=rja">HGDP</a> (25 Russians, 16 Adygei), 175 individuals from the <a href="http://www.google.ee/url?sa=t&rct=j&q=1000%20genomes%20project&source=web&cd=1&ved=0CCEQFjAA&url=http%3A%2F%2Fwww.1000genomes.org%2F&ei=spvBTommGZH24QTGldyUBA&usg=AFQjCNEcWW0DlYJ57GCGIoSnjeBsI7AVlQ&cad=rja">1000 Genomes Project</a> (83 British, 92 Finns)</span>
<span class="st">and 62 individuals from Yunusbayev et all. (2011) paper (14 Mordovians, 16 Nogays,13 Bulgarians,19 Ukrainians).</span><br />
<br />
<span class="st"> The ethnic distribution of the whole set would look as follows (ethnic groups<span style="background-color: white;"> <span style="color: red;">in red</span></span> need more participants/samples )<span style="background-color: white;"></span></span><br />
<br />
<br />
<table border="0" cellpadding="0" cellspacing="0" style="width: 128px;"><colgroup><col span="2" style="width: 48pt;" width="64"></col>
</colgroup><tbody>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="color: red; height: 15pt; width: 48pt;" width="64">Belarussian</td>
<td align="right" style="width: 48pt;" width="64">18</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Adygei</td>
<td align="right">16</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Armenians</td>
<td align="right">18</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Aszkenazi</td>
<td align="right">2</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Bulgarians</td>
<td align="right">13</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Chuvashs</td>
<td align="right">17</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Finns</td>
<td align="right">92</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">British</td>
<td align="right">83</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Georgians</td>
<td align="right">20</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Hungarian</td>
<td align="right">20</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="color: red; height: 15pt;">Latvian</td>
<td align="right">1</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Lezgins</td>
<td align="right">15<span style="background-color: white;"></span></td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Lithuanians</td>
<td align="right">27</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Mordovians</td>
<td align="right">14</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Nogays</td>
<td align="right">16</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Ossetians</td>
<td align="right">14</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="background-color: white; color: red; height: 15pt;">Norwegians</td>
<td align="right">2</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="color: red; height: 15pt;">East Germans</td>
<td align="right">7</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Others </td>
<td align="right">8</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="background-color: white; color: red; height: 15pt;">Poles</td>
<td align="right">18</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Romanians</td>
<td align="right">14</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Russians</td>
<td align="right">36</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="color: red; height: 15pt;">Swedish</td>
<td align="right">2</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Turks</td>
<td align="right">16</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Ukrainians</td>
<td align="right">30</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Uzbeks</td>
<td align="right">12</td>
</tr>
</tbody></table>
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEge5QAXYwLf4AGsNc-I7PIonFI3ajkOFJbYKi0vo1q3Ndo7fxD1TMvqab17EmU-9zrxIebtWHhnYuIr6QULOaJtCxrBUWTEBVLt0zSLD7RveuWgh3aH9Mgr7pzYquSHxJx4eNQ8ZhbaCMA/s1600/distro.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="257" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEge5QAXYwLf4AGsNc-I7PIonFI3ajkOFJbYKi0vo1q3Ndo7fxD1TMvqab17EmU-9zrxIebtWHhnYuIr6QULOaJtCxrBUWTEBVLt0zSLD7RveuWgh3aH9Mgr7pzYquSHxJx4eNQ8ZhbaCMA/s320/distro.jpg" width="320" /></a></div>
<br />
Another interesting characteristics of sample is that one of average inbreeding coefficient in each particular population, based on the observed
versus expected number of homozygous genotypes in given population.<br />
<br />
<br />
<table border="0" cellpadding="0" cellspacing="0" style="width: 292px;"><colgroup><col style="mso-width-alt: 5522; mso-width-source: userset; width: 113pt;" width="151"></col>
<col style="mso-width-alt: 5156; mso-width-source: userset; width: 106pt;" width="141"></col>
</colgroup><tbody>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt; width: 113pt;" width="151"><a href="http://www.blogger.com/blogger.g?blogID=7120134997435393696" name="RANGE!A1:B17">FID</a></td>
<td style="width: 106pt;" width="141">F-coefficient</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Lithuanian-average</td>
<td align="right">0.0158738</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Finn-average</td>
<td align="right">0.01375742</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">GBR_Orkney-average</td>
<td align="right">0.013074288</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Lezgin-average</td>
<td align="right">0.012808472</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Belorussian-average</td>
<td align="right">0.011024444</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">GBR_Cornwall-average</td>
<td align="right">0.010527961</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">GBR_Kent-average</td>
<td align="right">0.009641047</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Georgian-average</td>
<td align="right">0.00949285</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Turk-average</td>
<td align="right">0.0093435</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Hungarian-average</td>
<td align="right">0.007138795</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Adygei-average</td>
<td align="right">0.006826329</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Romanian-average</td>
<td align="right">0.006763092</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Russian-average</td>
<td align="right">0.006179208</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Uzbek-average</td>
<td align="right">0.005255747</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Armenian-average</td>
<td align="right">0.004329326</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Chuvash-average</td>
<td align="right">0.004147971</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;"><br /></td>
<td><br /></td>
</tr>
</tbody></table>
<br />
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhw9guOpnsL87LwYuTh9wAo9dD37EPpXsfunuQzxcQiEC-5h6f7ubhMUveqrgeoxxg__tQad4binxTsConnRM6yIR66YmSempYfHpJ21jRPGRhi2U0Nz9wgcK9Sq3-k5n3oFXrCrT8SuXk/s1600/inbreed.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="202" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhw9guOpnsL87LwYuTh9wAo9dD37EPpXsfunuQzxcQiEC-5h6f7ubhMUveqrgeoxxg__tQad4binxTsConnRM6yIR66YmSempYfHpJ21jRPGRhi2U0Nz9wgcK9Sq3-k5n3oFXrCrT8SuXk/s320/inbreed.jpg" width="320" /></a></div>
The following characteristic of MDLP - an average number of shared IBD segments per population is especially valuable for evaluating the genomic structure of population. I've limited the results to Slavic populations only. <br />
<br />
<br />
<br />
<table border="0" cellpadding="0" cellspacing="0" style="width: 128px;"><colgroup><col span="2" style="width: 48pt;" width="64"></col>
</colgroup><tbody>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt; width: 48pt;" width="64">Poles</td>
<td align="right" style="width: 48pt;" width="64">0.878788</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Belarusians</td>
<td align="right">0.722008</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Ukrainaians</td>
<td align="right">0.676113</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Russians</td>
<td align="right">0.561878</td>
</tr>
<tr height="20" style="height: 15.0pt;">
<td height="20" style="height: 15.0pt;">Lithuanians</td>
<td align="right">0.548961</td>
</tr>
</tbody></table>
<br />
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhvRvWDeo2a0DivdqaMf8cof6j3AbcRAjO02MP3aDRRKt5zXzj3bw7Gv1MSc1vFTqU9xUpuHnI6T-S06Ihpc6umwOVVzfCbJ8rsJzUt7BQm23irVcorEmTsz2vBnU4w0U5NL8vbGnhsCUs/s1600/ibd.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="192" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhvRvWDeo2a0DivdqaMf8cof6j3AbcRAjO02MP3aDRRKt5zXzj3bw7Gv1MSc1vFTqU9xUpuHnI6T-S06Ihpc6umwOVVzfCbJ8rsJzUt7BQm23irVcorEmTsz2vBnU4w0U5NL8vbGnhsCUs/s320/ibd.jpg" width="320" /></a></div>
<br />
<span class="st"> </span>
</div>
</div>Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com1tag:blogger.com,1999:blog-7120134997435393696.post-43317216737629934432011-11-04T15:44:00.000-07:002011-11-04T15:44:54.703-07:00The major revision of MDLP: adding Yunusbayev et all.2011 data<div dir="ltr" style="text-align: left;" trbidi="on">
Earlier this month i added Bulgarians, Ukrainians and Mordovians from the reference samples in Yunusbayev et all.2011 paper and calculated PCA loadings of new obtained <br />
<br />
As promised earlier, i have wasted a couple of hours on plotting PCA
loadings (from Eigensoft analysis of my MDL BGA project) in graphical
interface of indispensable R-package "<a href="http://biplotgui.r-forge.r-project.org/" target="_blank">BiplotGUI</a>". I've made a lot of efforts combining diffirent types of statistical tests into one meaningful illustration.<br />
<br />
Below are results of my experiments with Biplot.<br />
<br />
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiUqsj0mcOjO9goylJkDmIStd4JZRagAXTuaNxts1PuY9qbLg_n1uA8Hed0vIc9gIBjGKpUH7scaDT_DkIaywbktoVseMQJfEyY92nPSwWIOFSoutcKWso36h_rh5DyRFXsbIKhEA2nuHg/s1600/a2622254d4.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiUqsj0mcOjO9goylJkDmIStd4JZRagAXTuaNxts1PuY9qbLg_n1uA8Hed0vIc9gIBjGKpUH7scaDT_DkIaywbktoVseMQJfEyY92nPSwWIOFSoutcKWso36h_rh5DyRFXsbIKhEA2nuHg/s320/a2622254d4.jpg" width="320" /></a></div>
<br />
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEghP5RaNUja3ylwhWhlCdDhX58fX8Q8xWVGeYu7VCzCMn6lhxv68ya6WW4zHc5kT6L0UM147OUGqagLrZLXlS0hxhR1oMLw9oVkkD6HpcofRxapbrOtdUGWPt4CIt3G2h8GlRmNd5Pxq9c/s1600/pca.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="178" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEghP5RaNUja3ylwhWhlCdDhX58fX8Q8xWVGeYu7VCzCMn6lhxv68ya6WW4zHc5kT6L0UM147OUGqagLrZLXlS0hxhR1oMLw9oVkkD6HpcofRxapbrOtdUGWPt4CIt3G2h8GlRmNd5Pxq9c/s320/pca.jpg" width="320" /></a></div>
<br />
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg6GkvE86_C82fC7mWeJsCqr0nq45Cfdj8iJsPbf4ksI71EfPup4-U-tLfTb5bM1TVuv3btb9ltJ8_1msQvhjqqv7HNT5K8pTOuKbx7mNV9dGhk6sCq9oC1t7bXg-PV9G9XGabeU9SE9kI/s1600/PCA-comb.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="248" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg6GkvE86_C82fC7mWeJsCqr0nq45Cfdj8iJsPbf4ksI71EfPup4-U-tLfTb5bM1TVuv3btb9ltJ8_1msQvhjqqv7HNT5K8pTOuKbx7mNV9dGhk6sCq9oC1t7bXg-PV9G9XGabeU9SE9kI/s320/PCA-comb.jpg" width="320" /></a></div>
<br />
<br />
Another cool feature of BiplotGUI is that it fully supports <b>rgl</b>,
which is a 3D visualization system based on OpenGL. It provides a medium
to high level interface for use in R, currently modelled on classic R
graphics, with extensions to allow for interaction and creation of 3D
animations/movies.<br />
<br />
I've not figured yet how it works, but the next time i will be doing PCA
analysis, i'll try to make 3D rotating animations for members of my
project.
<br />
<br />
<div class="separator" style="clear: both; text-align: center;">
<iframe allowfullscreen='allowfullscreen' webkitallowfullscreen='webkitallowfullscreen' mozallowfullscreen='mozallowfullscreen' width='320' height='266' src='https://www.youtube.com/embed/CTwgNHCnT2A?feature=player_embedded' frameborder='0'></iframe></div>
<br /></div>Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com1tag:blogger.com,1999:blog-7120134997435393696.post-35767433749493821792011-11-04T14:19:00.001-07:002011-11-04T15:54:22.251-07:00(Via) DODECAD:Comparing different ADMIXTURE runs using Zombies<div dir="ltr" style="text-align: left;" trbidi="on">
<div style="text-align: justify;">
Dienekes Pontikos of DODECAD BGA project <a href="http://dodecad.blogspot.com/2011/10/comparing-different-admixture-runs.html">was using our MDLP calculator (based on DIYDodecad methodological paradigma) as proof concept</a> for comparing/mapping the Eurasian components inferred from the Dodecad-dv3 dataset (West Asian, West European, East European, Mediterranean, Northeast Asian, Southeast Asian) against MDLP components (Scandinavian,Volga_Region, Altaic, Celto_Germanic, Caucassian_Anatolian_Balkanic, Balto_Slavic, North_Atlantic).</div>
<div style="text-align: justify;">
<br /></div>
<div style="text-align: justify;">
This is what he did :</div>
<div style="text-align: justify;">
<br /></div>
<blockquote class="tr_bq">
<div style="text-align: justify;">
<span style="font-size: x-small;">".. To compare components across <b>different projects</b>;
there has been a proliferation of different ancestry projects since the
launching of Dodecad nearly a year ago, and since all of them slightly
different individuals/SNPs/terminology, it is quite useful to be able to
gauge how one component from one project maps onto other components in
other projects. As proof of concept, I took the <a href="http://magnusducatus.blogspot.com/2011/08/i-have-modified-diydodecad-calculator.html">MDLP</a> calculator from the <a href="http://magnusducatus.blogspot.com/">Magnus Ducatus Lituaniae Project</a> and generated 50 zombies for each of its 7 ancestral components:</span></div>
<blockquote class="tr_bq">
<div>
<div>
<ol>
<li><span style="font-size: x-small;">Scandinavian</span></li>
<li><span style="font-size: x-small;">Volga_Region</span></li>
<li><span style="font-size: x-small;">Altaic</span></li>
<li><span style="font-size: x-small;">Celto_Germanic</span></li>
<li><span style="font-size: x-small;">Caucassian_Anatolian_Balkanic</span></li>
<li><span style="font-size: x-small;">Balto_Slavic</span></li>
<li><span style="font-size: x-small;">North_Atlantic</span></li>
</ol>
</div>
</div>
</blockquote>
<span style="font-size: x-small;"> I
then inferred the ancestry of the MDLP zombies using Dodecad v3, and
vice versa. Since Dodecad v3 also includes populations (e.g., Africans)
not considered by MDLP, <b>I did not try to map those onto MDLP.</b></span></blockquote>
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhKqhXtCO7gTMvcl0O_lfNghrf20yGtd5xBIiRBvngmqjRKlNYmtCcXblzqSETVEMnGzLNAeiThv1MSgDS0C9NDXdjGOFE9mMo8_ugIYOPmeNP3ELQfcqb81d3v0RVQXqAuh4CU0t0nNfU/s400/_7.png" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" height="204" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhKqhXtCO7gTMvcl0O_lfNghrf20yGtd5xBIiRBvngmqjRKlNYmtCcXblzqSETVEMnGzLNAeiThv1MSgDS0C9NDXdjGOFE9mMo8_ugIYOPmeNP3ELQfcqb81d3v0RVQXqAuh4CU0t0nNfU/s320/_7.png" width="320" /></a></div>
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<blockquote class="tr_bq">
<div>
<span style="font-size: x-small;">I will comment on the MDLP-to-dv3 mapping:</span></div>
<div>
<ol>
<li><span style="font-size: x-small;">The MDLP "Scandinavian" component appears to be West/East European with a little Mediterranean and a little Northeast Asian</span></li>
<li><span style="font-size: x-small;">The MDLP "Volga_Region" component appears to be East European with some Northeast Asian</span></li>
<li><span style="font-size: x-small;">The
MDLP "Altaic" component is West Asian+Northeast Asian+Southeast Asian.
Note that in Dodecad v3, the Northeast Asian component peaks at Chukchi,
Nganasan, and Koryak, and most other east Eurasian populations have
much less of it</span></li>
<li><span style="font-size: x-small;">The MDLP "Celto-Germanic" component is
(surprisingly) Mediterranean-dominated. One possible interpretation is
that in the context of MDLP this captures one aspect of the difference
between Southwestern and Northeastern Europe -higher Mediterranean in
the former-, whereas the...</span></li>
<li><span style="font-size: x-small;">... MDLP "North-Atlantic" component
seems to be entirely West European, and is capturing a different aspect
of east-west variation in Europe. </span></li>
<li><span style="font-size: x-small;">The MDLP "Balto-Slavic" appears the reverse of the "Celto-Germanic" with lower Mediterranean and reversed East/West European</span></li>
<li><span style="font-size: x-small;">Finally,
the MDLP "Caucassian_Anatolian_Balkanic" component is predictably
mainly West Asian, but with a little Mediterranean and Southwest Asian
as well</span></li>
</ol>
<span style="font-size: x-small;">A different way of comparing the different components
is to include them all in a joint MDS plot, or calculate various types
of distances between them (e.g., Fst). </span></div>
<div>
<span style="font-size: x-small;"><br /></span></div>
<span style="font-size: x-small;">For
example, the first couple of dimensions are dominated by the
African/Asian components of Dodecad v3 that are not present in MDLP.Notice, however, the position of "Altaic", right where one might expect to find it between West and East Eurasians.</span></blockquote>
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<blockquote class="tr_bq">
<span style="font-size: x-small;">It appears that the "North_Atlantic" component may be centered on a small number of related individuals</span>."</blockquote>
<br />
PS. Our MDLP calculator has been occasionally used by various people, and thus results arecurrently being disseminated over the large number of the different Internet communities of DNA-genealogy/molecular anthroplogy's hobbysts. We are going to collect the results made publicly available by those hobbysts and out them into one spreadsheet for the futher analysis. <br />
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</div>Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com0tag:blogger.com,1999:blog-7120134997435393696.post-61970747752395719592011-10-06T14:50:00.000-07:002011-10-06T14:50:54.216-07:00Analyzing admixture in phased v.unphased dataset<div dir="ltr" style="text-align: left;" trbidi="on">
Determination of haplotype phase is becoming increasingly important as
we enter the era of large-scale sequencing because many of its
applications, such as imputing low-frequency variants and characterizing
the relationship between genetic variations in different populations. Haplotype phase can be
generated through laboratory-based experimental methods, or it can be
estimated using computational approaches. We assess the haplotype
phasing method that is aravailable in BEAGLE software, focusing in particular on using its output in ADMIXTURE analysis.<br />
<br />
For simplicity's sake we have selected individuals from "Balto-Slavic" cluster (the cluster attribution of individuals were inferred from Dienekes's <a href="http://dienekes.blogspot.com/2010/12/human-genetic-variation-124-clusters.html">Mclust </a>using 11 MDS dimension), which is the major cluster of our project. Here is an all inclusive list of IDs for selected participants of our project:<br />
<br />
<b>V158<br />V157<br />V160<br />V202<br />V169<br />V170<br />V171<br />V174<br />V176<br />V177<br />V180<br />V181<br />V188<br />V189<br />V196<br />V205<br />V208<br />V211<br />V215<br />V218<br />V220<br />V221<br />V222<br />V228<br />V225<br />V232<br />V236<br />V237<br />V235<br />V231<br />V244<br />V246<br />V238</b><br />
<br />
<br />
<br />
<br />
<br />
<br />
We had thinned the genotype data of selected individuals to c.100 000 SNPs, removing SNPs in strong LD and low quality SNps. After that we used <a href="http://www.cs.columbia.edu/%7Egusev/germline/">GERMLINE pipeline for phasing PLINK format data with BEAGLE and processing in GERMLINE</a> (phasing was performed in a homologous populations), Then, in order to assess possible discrepancies between phased and unphased data, we performed ADMIXTURE analysis (with 4 assumed clusters K=4) separately for original unphased dataset and BEAGLE-phased dataset.<br />
<br />
To our surprise, we haven't be able to find expected signficant differences between phased and unphased multi -SNP markers genotypes (the range of difference is c.1-5%).<br />
<br />
Unphased data:<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgfFrn6mJ2XVzZlp-Sny8b4r_HDDTdOYwz_H13yz97bdSEaSli2PjGHWaRODmIWittRh8t6FMAFGd9SknlfH4bNt1q3pneKMiIXZllkOvMukN2f7n6JxMYgx_5-a7cyeXg76DrWV1YjgeQ/s1600/unphased.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="640" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgfFrn6mJ2XVzZlp-Sny8b4r_HDDTdOYwz_H13yz97bdSEaSli2PjGHWaRODmIWittRh8t6FMAFGd9SknlfH4bNt1q3pneKMiIXZllkOvMukN2f7n6JxMYgx_5-a7cyeXg76DrWV1YjgeQ/s640/unphased.jpg" width="275" /></a></div>
Phased data:<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiZWGqo7X30G-vqVYH8y3cpY87t4T092yhShaWMLoQDHWbH4s4hy9uiKEIRENy9nSmIZUf1RzFBjzxD44_M4oLyRoXEZiB4nq2G6enjzI2Zi0aOiXONaRyUDyqZFZYeKPqaaxM1Rb0EZi8/s1600/phased.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="640" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiZWGqo7X30G-vqVYH8y3cpY87t4T092yhShaWMLoQDHWbH4s4hy9uiKEIRENy9nSmIZUf1RzFBjzxD44_M4oLyRoXEZiB4nq2G6enjzI2Zi0aOiXONaRyUDyqZFZYeKPqaaxM1Rb0EZi8/s640/phased.jpg" width="304" /></a></div>
Spreadsheet with ADMIXTURE results can be found <a href="https://docs.google.com/spreadsheet/ccc?key=0Aqn7iMc2P-yQdFpZbEVmWVE0ZGd3UWRoYU42a3hDNWc&hl=en_US">here</a>.</div>
Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com0tag:blogger.com,1999:blog-7120134997435393696.post-21349234735100120092011-10-04T12:55:00.000-07:002011-10-04T13:44:13.610-07:00Simulated SNP-populations of MDLP<div dir="ltr" style="text-align: left;" trbidi="on">Yesterday I had set out to repeat "simulation" experiments with a SNP dataset of my project's dataset, using PLINK's simulation techniques <a href="http://dodecad.blogspot.com/2011/05/how-to-create-zombies-from-admixture.html">first described (in terms of <b>population genetics</b>) by Dienekes</a> (the analogous experiments were performed by <a href="http://www.harappadna.org/2011/07/admixture-supervised-zombies-vs-unsupervised/">Harappa DNA</a> BGA project and Eurogenes <a href="http://bga101.blogspot.com/2011/09/genetic-substructures-across-west.html">BGA project</a>).<br />
Synthetic "ancestral" populations (<b>Altaic, Anatolian-Balkanian, Balto-Slavic, North-Atlantic, Scandinavian, Volga-Uralic and Celto-Germanic</b>) were simulated using standard PLINK's simulation routine, with each ""synthetic" population including 5 generated synthetic individuals: <br />
<h5 style="font-weight: normal; text-align: left;">plink --simulate wgas1.sim --make-bed --out sim11</h5><h5 style="font-weight: normal; text-align: left;">plink --simulate wgas2.sim --make-bed --out sim12</h5><h5 style="text-align: left;"><span style="font-weight: normal;">etc. </span>..</h5><h5></h5>In data simulation, we assumed that each of 7 clusters defined by specific combination of allele frequencies of c.100000 Snps (obtained from ADMIXTURE K=7 run under unsupervised model) represents one ancestral pupulation. <br />
<br />
Since I was interested in PCA loadings of "ancestral" populations, i used <a href="http://genepath.med.harvard.edu/%7Ereich/Software.htm">Eigensoft </a>for explicit modeling differences between different components" along continuous axes of variation. The calculated PCA loadings were then visualized as interactive biplot in R-package <a href="http://genepath.med.harvard.edu/%7Ereich/Software.htm">BiplotGUI </a>using the following Biplot's command:<br />
<br />
> Biplots(Data = PCA[, -1], groups = [, 1])<br />
<br />
Afterwards i performed three statistical tests on imported PCA loadings: linear regression, circular regression and procrusted analysis. <br />
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</div>Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com1tag:blogger.com,1999:blog-7120134997435393696.post-16105598460798246442011-10-04T11:27:00.000-07:002011-10-04T11:29:31.147-07:00MDLP modification of DIYDodecad calculator: additional instructions/ideas<div dir="ltr" style="text-align: left;" trbidi="on">I have come up with another idea of how to use <a href="http://magnusducatus.blogspot.com/2011/08/projects-update-results-for.html">the estimated frequencies of my project for inferring the origin of shared HIR segments</a>. Suppose, for example, that a Lithuanian/Belorussian and a Norwegian share some HIR segment. This could be:<br />
<br />
1)Balto-Slavic-like ancestry in the Norwegian individual<br />
2)Scandinavian-like ancestry in the Lithuanian individual<br />
3)third party ancestry in both individuals<br />
<br />
Using <b>byseg 500 50</b> mode in <a href="http://dodecad.blogspot.com/2011/08/do-it-yourself-dodecad-v-20.html"><b>DIYDodecad</b>,</a> AncestryFinder file, and MDLP allele frequencies, i was able to predict the origin of the HIR segment by picking one of three scenarios:<br />
<br />
1) if the Lithuanian sees an excess of Scandinavian, then he should pick the second scenario<br />
2) if he sees nothing unremarkable, the first one<br />
3) if an excess of some component (relatively) low in both Lithuanian and Norwegian (e.g., Caucassian-Anatolian), the third.<br />
<br />
<br />
After analyzing my "Scandinavian" "matches" from AF's file, i can conclude that DIYDodecad analysis (in byseg mode) reveals the presence of all three possible scenarios:<br />
<br />
<b><u>Scenario nr.2 (Balto-Slavic-like ancestry in the Scandinavian individual)</u></b><br />
X Sweden Sweden United States United States 1 156.4 160 3.6 5.6<br />
<b><u>60%-Scenario nr.1 (Scandinavian-like ancestry in the Balto-Slavic individual)</u></b><br />
X Denmark Denmark Denmark Denmark 1 87.9 94.3 6.4 6.3<br />
<b>Scenario nr.1 (Scandinavian-like ancestry in the Balto-Slavic individual)</b><br />
X Norway Norway Norway Norway 1 62.1 65.4 3.3 5<br />
<b><u>Scenario nr.1 (Scandinavian-like ancestry in the Balto-Slavic individual)</u></b><br />
Anonymous0454 Finland Finland Finland Finland 1 104.8 110.3 5.5 6.4<br />
<b><u>Scenario nr.2 (Balto-Slavic-like ancestry in the Scandinavian individual)</u></b><br />
X Sweden Not Provided Not Provided Not Provided 2 82.2 88.1 5.9 5<br />
<b><u>60%-Scenario nr.2 (Balto-Slavic-like ancestry in the Scandinavian individual)</u></b><br />
X Sweden Sweden United States United States 3 174.9 178.1 3.2 5<br />
<b><u>80%-Scenario nr.2 (Balto-Slavic-like ancestry in the Scandinavian individual)</u></b><br />
Anonymous0353 Denmark Denmark Denmark Denmark 3 68.4 73.3 4.9 8.1<br />
<b><u>50%-Scenario nr.2 (Balto-Slavic-like ancestry in the Scandinavian individual)</u></b><br />
Anonymous0245 Denmark Denmark Denmark Denmark 4 70.5 77.3 6.8 5.3<br />
<br />
<b><u><a href="http://en.wikipedia.org/wiki/Human_leukocyte_antigen" target="_blank"><br />
HLA-MHC group</a> -Scenario III - third party (Celto-Germanic) ancestry in both individuals</u></b><br />
X Sweden Sweden United States United States 6 25.8 34.2 8.4 5.4<br />
X Sweden Denmark United States United States 6 27.6 34.5 6.9 5.1<br />
Anonymous0207 Sweden Sweden Not Provided Not Provided 6 25.6 34.1 8.5 5.3<br />
X Norway Not Provided Belgium Not Provided 6 29.7 36.1 6.4 5.3<br />
Anonymous0370 Sweden Sweden Not Provided Sweden 6 30.7 36.6 5.9 5.4<br />
X Denmark Denmark Denmark Denmark 6 25.6 35.5 9.9 5.9<br />
Anonymous0439 Denmark Not Provided United States Hungary 6 26.3 36 9.7 6<br />
X Denmark Denmark Denmark Denmark 6 26 34 8 5.1<br />
X Norway Norway Norway Norway 6 25.6 34.2 8.6 5.6<br />
<br />
<b><u>Chr14. group - 70%-Scenario nr.2 (Balto-Slavic-like ancestry in the Scandinavian individual)</u></b><br />
Anonymous0001 Norway Norway Norway Norway 14 38 48.8 10.8 6.5<br />
Anonymous0037 Sweden Norway United States United States 14 39.2 48 8.8 5.1<br />
<br />
<b><u>Scenario nr.1 (Scandinavian ancestry in the Balto-Slavic individual)</u></b><br />
Anonymous0002 Denmark Denmark United States United States 15 43.9 51.3 7.4 6<br />
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</div>Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com2tag:blogger.com,1999:blog-7120134997435393696.post-9824538504376215572011-08-27T13:57:00.000-07:002011-08-27T13:57:36.251-07:00<div dir="ltr" style="text-align: left;" trbidi="on"><div style="text-align: justify;">I have modified <a href="http://dodecad.blogspot.com/2011/08/do-it-yourself-dodecad-v-20.html">DIYDodecad calculator v2.0 </a>for my BGA project (MDLP). If you want to analyze your genotype using allelic frequencies, estimated from the <a href="http://magnusducatus.blogspot.com/2011/08/projects-update-results-for.html">latest K=7 Admixture run,</a> you should download MDLP.zip file (File -> Download original) and extract its contents to the directory of DIYDodecad. </div><div style="text-align: justify;">Then launch the MDLP add-on by entering the command <b>DIYDodecadWin MDLP.par </b><br />
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You can download MDLP add-on for DIYDodecad calculator <a href="https://docs.google.com/viewer?a=v&pid=explorer&chrome=true&srcid=0B6n7iMc2P-yQMWYwODYwMjctYWVmNS00YTlmLWJmYTctYTc5Mjc3NWI4NWY3&hl=en_US">here</a>.</div><br />
</div>Project "Magnus Ducatus Lituaniae"http://www.blogger.com/profile/06764361071403376842noreply@blogger.com2