Tag: African Ancestry Project

Any Tutsi genotypes around?

By Razib Khan | July 3, 2011 12:05 pm

If anyone has, or knows of, Tutsi genotypes that I could analyze for the African Ancestry Project, could you please email me at africanancestryproject-at-gmail-dot-com? I want to ascertain the extent of genetic differences between Tutsi and Bantu populations, and whether the source of the Tutsi were Nilotic or Cushitic.

CATEGORIZED UNDER: Genetics, Genomics

ADMIXTURE, African Ancestry Project, and confirmation bias

By Razib Khan | May 2, 2011 1:29 pm

I’ve been running the African Ancestry Project for a while now on the side on Facebook. But it’s getting unwieldy, so I finally set up the website. The main reason I started it up is that there have been complaints for a while now of problems with the 23andMe “ancestry painting” and such for some African groups. For example, a Nubian might be 70% “European.” One might argue that this is due to Arab admixture, but this is clearly not so if you look at the PCA plot. What’s going on? Probably a problem with the reference populations (only Yoruba for Africa), ascertainment bias in the chip (they’re tuned to European variation), and the fact that African genetic variance can cause some issues. I don’t know. But the problem has been persistent, and since most of the other genome blogging projects exclude Africans because they’re so genetically diverse I decided to take it on.

Three groups of people have submitted:

– People of the African Diaspora in the New World

– People from Africa, disproportionately Northeast Africans (Horn of African + Nubia, etc.)

– People of some suspected or known minor component of African ancestry

I’m at ~70 participants now. As one reference population set I’ve been using a subset of Henn et al. as well as some populations from Behar et al. I call this my “thin” set since there are only ~40,000 SNPs. A “thick” set has on the order of 300-400 thousand markers. But fewer populations. I’ve been putting the AAP members through ADMIXTURE in batches of 10, but I also run them all together sometimes for apples-to-apples comparisons. Yesterday I ran AF001 to AF070 from K = 2 to K = 14, unsupervised, with the thin reference. If you want to see all the results, go here. Doing all this myself over and over has given me some intuition as to the pitfalls in this sort of analysis.  Especially in the area of confirmation bias.

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CATEGORIZED UNDER: Genetics, Genomics
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