Konrad Karczewski and colleagues from Stanford have put together a very handy set of online tools for analysing personal genomic data. The tools work within your browser (Chrome and FireFox only, so the ~18% of you who continue to use Internet Explorer now have yet another incentive to change), meaning your genetic data never actually leaves your computer. They currently work with raw, unzipped data from 23andMe and Lumigenix. The tools were developed initially for use in Stanford’s pioneering Genomics and Personalized Medicine elective course for graduate and medical students, in which students had the opportunity to explore their own 23andMe or Lumigenix data. Karczewski has some background over at his personal blog.
Once you’ve pointed Interpretome to your raw data file (top right-hand corner) and assigned your ancestry you can start playing with the tools – for instance, you can calculate your type 2 diabetes risk or warfarin dose, or estimate the fraction of your genome inherited from Neandertal (see image above for my result). A caveat: I’m writing this post without carefully checking the output from any of these analyses, so as always in personal genomics, interpret your results with caution.
I suspect one of the more popular suites of tools will be the PCA package, which allow you to place your genetic data in the context of worldwide patterns of genetic variation. Here the authors have pre-calculated the crucial information (the PCA loadings) for each SNP in the 23andMe data-set, allowing them to very quickly calculate your position in a worldwide genetic map containing thousands of individuals. Here’s my 23andMe v3 data (black square) projected onto a genetic map of Europe created with POPRES samples. The picture isn’t quite as pretty as the one in the 2008 Nature paper using the same cohort – the Interpretome team
haven’t applied the same extensive filters to remove extraneous features from the data have had to work with the smaller number of SNPs that overlap with the 23andMe v3 chip, and you need to plot PC1 vs PC4 before you start seeing something that resembles a map of Europe – but it’s enough to give you a sense as to where you fit. I was unsurprised to find myself sitting smack in the middle of the British cluster:
Anyway, go and check it out, and send it to your friends. We’re delighted to see such a handy package released free to the public – kudos to everyone involved in putting the website together. We’ll likely be posting a more thorough review of the site once we’ve had time to test the tools out on a range of Genomes Unzipped data-sets.