{"id":38787,"date":"2011-03-17T22:34:30","date_gmt":"2011-03-18T06:34:30","guid":{"rendered":"http:\/\/blogs.discovermagazine.com\/gnxp\/?p=10360"},"modified":"2011-03-17T22:34:30","modified_gmt":"2011-03-18T06:34:30","slug":"looking-for-relatedness-in-the-hapmap-gujaratis","status":"publish","type":"post","link":"https:\/\/www.razib.com\/wordpress\/2011\/03\/17\/looking-for-relatedness-in-the-hapmap-gujaratis\/","title":{"rendered":"Looking for relatedness in the HapMap Gujaratis"},"content":{"rendered":"

Recently I was looking at a 3-D PCA animation which Zack generated<\/a> from the Harappa Ancestry Project<\/a> data set. Click the link and come back. Notice the outlier clusters?\u00a0The Burusho are straightforward, they seem to have low levels of Tibetan admixture. But what about the Gujarati cluster?<\/strong> Again, we see what we’ve seen before, the fractioning out of the Gujaratis in PCA into two groups, one a tight cluster, and the other relatively widely distributed. This prompted me to look more closely at the HapMap Gujarati sample. Today I was exploring the question with Plink’s identity-by-descent<\/a> feature. First I’ll start out with a smaller data set, my family (father, mother, sibling 1, sibling 2, and myself), and an Indian (from Uttar Pradesh) and Pakistani as unrelated individuals. I merged out 23andMe derived genotypes, and with ~900,000 markers calculated pairwise IBD:<\/p>\n<\/p>\n

.\/plink –bfile IBDControl –genome<\/p>\n

Here are the relevant results:<\/p>\n

Individual 1<\/strong>
\nIndividual 2<\/strong>
\nZ0<\/strong>
\nZ1<\/strong>
\nZ2<\/strong>
\nPI_HAT<\/strong>
\nDST<\/strong>
\nPPC<\/strong>
\nRATIO<\/strong><\/p>\n

Indian
\nFather
\n0.768
\n0.027
\n0.205
\n0.218
\n0.760<\/em>
\n0.160
\n1.940<\/p>\n

Indian
\nMother
\n0.782
\n0.010
\n0.209
\n0.214
\n0.759<\/em>
\n0.026
\n1.886<\/p>\n

Indian
\nRazib
\n0.767
\n0.032
\n0.202
\n0.218
\n0.759<\/em>
\n0.500
\n2.000<\/p>\n

Indian
\nSibling1
\n0.769
\n0.025
\n0.206
\n0.219
\n0.760<\/em>
\n0.198
\n1.949<\/p>\n

Indian
\nSibling2
\n0.766
\n0.032
\n0.203
\n0.219
\n0.760<\/em>
\n0.685
\n2.030<\/p>\n

Indian
\nPakistani
\n0.781
\n0.017
\n0.203
\n0.211
\n0.758<\/em>
\n0.533
\n2.005<\/p>\n

Father
\nMother
\n0.776
\n0.018
\n0.207
\n0.215
\n0.759<\/em>
\n0.284
\n1.965<\/p>\n

Father
\nRazib
\n0.002
\n0.777
\n0.221
\n0.610
\n0.851<\/em>
\n1.000
\n450.800<\/p>\n

Father
\nSibling1
\n0.001
\n0.785
\n0.214
\n0.606
\n0.850<\/em>
\n1.000
\n898.800<\/p>\n

Father
\nSibling2
\n0.002
\n0.779
\n0.220
\n0.609
\n0.851<\/em>
\n1.000
\n643.143<\/p>\n

Father
\nPakistani
\n0.778
\n0.019
\n0.203
\n0.213
\n0.758<\/em>
\n0.201
\n1.950<\/p>\n

Mother
\nRazib
\n0.002
\n0.788
\n0.211
\n0.605
\n0.849<\/em>
\n1.000
\n639.429<\/p>\n

Mother
\nSibling1
\n0.002
\n0.781
\n0.218
\n0.608
\n0.850<\/em>
\n1.000
\n639.857<\/p>\n

Mother
\nSibling2
\n0.002
\n0.782
\n0.216
\n0.607
\n0.850<\/em>
\n1.000
\n447.900<\/p>\n

Mother
\nPakistani
\n0.779
\n0.020
\n0.201
\n0.211
\n0.758<\/em>
\n0.052
\n1.904<\/p>\n

Razib
\nSibling1
\n0.183
\n0.408
\n0.409
\n0.613
\n0.866<\/em>
\n1.000
\n11.386<\/p>\n

Razib
\nSibling2
\n0.194
\n0.432
\n0.374
\n0.590
\n0.858<\/em>
\n1.000
\n11.491<\/p>\n

Razib
\nPakistani
\n0.781
\n0.016
\n0.203
\n0.211
\n0.758<\/em>
\n0.933
\n2.095<\/p>\n

Sibling1
\nSibling2
\n0.236
\n0.412
\n0.351
\n0.557
\n0.849<\/em>
\n1.000
\n9.413<\/p>\n

Sibling1
\nPakistani
\n0.777
\n0.024
\n0.199
\n0.211
\n0.758<\/em>
\n0.327
\n1.973<\/p>\n

Sibling2
\nPakistani
\n0.774
\n0.024
\n0.202
\n0.214
\n0.758<\/em>
\n0.443
\n1.991<\/p>\n

You can infer some things without even knowing what the columns mean. Notice that there are differences between parent-child, sibling-sibling, and unrelated comparisons. The distance measure, DST, is basically exactly the same as the genome-wide comparison in 23andMe. Either the web app is running Plink, or, it’s using the …<\/p>\n","protected":false},"excerpt":{"rendered":"

Recently I was looking at a 3-D PCA animation which Zack generated from the Harappa Ancestry Project data set. Click the link and come back. Notice the outlier clusters?\u00a0The Burusho are straightforward, they seem to have low levels of Tibetan admixtur…<\/p>\n","protected":false},"author":12,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4,82,1127],"tags":[],"class_list":["post-38787","post","type-post","status-publish","format-standard","hentry","category-genetics","category-genomics","category-gujaratis"],"_links":{"self":[{"href":"https:\/\/www.razib.com\/wordpress\/wp-json\/wp\/v2\/posts\/38787","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.razib.com\/wordpress\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.razib.com\/wordpress\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.razib.com\/wordpress\/wp-json\/wp\/v2\/users\/12"}],"replies":[{"embeddable":true,"href":"https:\/\/www.razib.com\/wordpress\/wp-json\/wp\/v2\/comments?post=38787"}],"version-history":[{"count":3,"href":"https:\/\/www.razib.com\/wordpress\/wp-json\/wp\/v2\/posts\/38787\/revisions"}],"predecessor-version":[{"id":38950,"href":"https:\/\/www.razib.com\/wordpress\/wp-json\/wp\/v2\/posts\/38787\/revisions\/38950"}],"wp:attachment":[{"href":"https:\/\/www.razib.com\/wordpress\/wp-json\/wp\/v2\/media?parent=38787"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.razib.com\/wordpress\/wp-json\/wp\/v2\/categories?post=38787"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.razib.com\/wordpress\/wp-json\/wp\/v2\/tags?post=38787"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}