More on Interpretome

First, let me start off by saying thanks to everyone that has explored their data on Interpretome so far. We’ve had a tremendous response to the site and I couldn’t be more thrilled. I wanted to provide an update on certain perspectives I’ve gotten from scouring the web for reactions to the analyses on the site.

I’m very proud to be picked up by Genomes Unzipped, Genome Web, Genomics Law Report, Discover Blog, and the folks at Genomes Are Us, who made a handy YouTube tutorial for the site. Thanks everyone!

It seems that many have enjoyed the Ancestry and Neandertal analyses, and to be honest, these are some my favorites too! They truly are a fascinating look into the role of ancient DNA and human migration patterns throughout history. Plotting yourself on a world/continent map can really give a perspective on where you’ve come from. My (not surprising) Polish ancestry jumps out on the POPRES dataset, clustering among Polish and Northern Europeans.

For those looking to explore their own, for most of the datasets, plotting PC1 vs. PC2 with any number of SNPs (the more, the better) should give good results, assuming you are somewhat similar to at least one of the populations in that reference panel. This means that Africans will likely find interesting results from the African PCA, but it is uninterpretable for Europeans. (As an aside, the POPRES dataset is best run with PC1 vs. PC4 and using the relevant platform, 43K for v2 and 74K for v3).

For the Chromosome Painting, at present, there is no “right” set of parameters. We use a heuristic/approximation algorithm to determine the ancestry tracks and we are actively developing more robust methods (as well as adding more distinct, i.e. less admixed reference populations). The challenge is to provide an accurate tool that can be run in your own browser (without too much computing power or sophisticated custom software). At the moment, the Hapmap 2 painting should work reasonably well: tuning the parameters will affect the sensitivity, at the cost of some noise.

Also coming soon is a new method to illustrate disease risk analysis, grouping SNPs by disease to visualize them easier. While we don’t intend to provide any actual predictive analysis, our mission is to provide the tools needed for anyone to explore their genome. We hope that this will educate the public (including clinicians and scientists as well as hobbyists) about the power/potential power/limitations of a personal genome and enable individuals to do and share their own custom analysis.


7 Responses to “More on Interpretome”

  1. June 23, 2011 at 6:10 am

    Hi Konrad–Can you tell me what the color codes are on the Neandertal scale? And I saw someone reference a high value in a HapMap individual, but I haven’t had time to track that down. Do you know what value that is on your display? I may need to change my avatar from Simpsonian to Neandertal….

  2. June 23, 2011 at 5:42 pm

    The color codes are fairly arbitrary; we based it on the highest we’d seen so far (at the time 19). Since then, I’ve heard of up to 26. The Neandertal exercise really just counts the number of putatively “Neandertal-derived” alleles in a personal genome. There is no interpretation in the gauge, but just a fun way to represent the data.

  3. June 23, 2011 at 6:57 pm

    Thanks Konrad. I’m still considering starting a Neandertal rights support group, and political PAC. Maybe I’ll try to collect all the people at my number and higher (apparently I’m not the highest…whew…) and see what we can do about that….Heh.

  4. 4 DLS
    July 3, 2011 at 5:12 pm

    What’s “average” on the Neandertal gauge? I’m half Ashkenazy Jew and half Scots Irish English, and scored a measly 6 “Neandertal” alleles. But people say I look Neandertal… 🙂

  5. July 5, 2011 at 1:03 pm


    We haven’t determined a true “average” yet for each population, but in our experience, it seems that the average for Europeans is in the 5-10 range.

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