I am using several datasets in the public domain for my reference population samples. HapMap is one of those datasets.
According to its website,
The goal of the International HapMap Project is to develop a haplotype map of the human genome, the HapMap, which will describe the common patterns of human DNA sequence variation. The HapMap is expected to be a key resource for researchers to use to find genes affecting health, disease, and responses to drugs and environmental factors. The information produced by the Project will be made freely available.
In the first phase, it genotyped
30 Yoruba adult-and-both-parents trios from Ibadan, Nigeria, 30 trios of U.S. (Utah) residents of northern and western European ancestry, 44 unrelated individuals from Tokyo, Japan and 45 unrelated Han Chinese individuals from Beijing, China.
In their HapMap phase 3 release #3 (NCBI build 36, dbSNP b126), there are 1,397 samples with about 1,457,897 SNPs each.
I removed related individuals as well as individuals whose genomes were too similar. This left me with a total of 1,149 samples with about 474,606 SNPs in common with 23andme's version 2 data.
Since we are not interested in Native American ancestry, I also removed 58 Mexican samples, thus leaving me with 1,091 samples.
Here are the samples I am using from the HapMap data:
| Ethnicity | Region | Count |
|---|---|---|
| African Americans | Africa | 48 |
| European Americans (Utahns) | Europe | 111 |
| Han Chinese | East Asia | 137 |
| US Chinese | East Asia | 106 |
| Gujaratis | South Asia | 98 |
| Japanese | East Asia | 113 |
| Kenyan Luhya | East Africa | 101 |
| Maasai | East Africa | 135 |
| Tuscans | Europe | 102 |
| Yoruba | West Africa | 140 |
The region assignments are mine to aid me in the analysis, by including/excluding samples by region or by aggregating results by region to find patterns etc.
It was easiest to use the HapMap data since it's available for download in Plink format.
7 Comments.