Genome Interpretation 2.0

In the race for the $1,000 genome, the issue of the $1,000,000 interpretation has not been forgotten. Combing through millions of variants in a personal genome has presented numerous challenges for all parties involved: the physician looking to add genomic measurements to inform their diagnoses, the patients trying to figure out what they should be worried about, and the hobbyists interested in what their DNA means to them. Direct-to-consumer genetic testing companies such as 23andme, Lumigenix, and Navigenics offer a glimpse into the interpretation of a genome. These companies curate literature on gene-trait associations and provide attractive user interfaces to navigating a personal genotype. However, the interpretations offered by these companies often differ, not because of inherent differences in technologies, but in which variants they choose consider in their calculations. While many have taken this fact to indicate a weakness of the genetic testing industry (and indeed, it is one that needs to be addressed), it is also a reflection of the dynamic nature of the field.

Meanwhile, this past Spring, I was once again involved with Stanford’s Personalized Medicine and Genomics course, a course aimed at bringing genetics into the clinic, explaining the utility of these tests, as well as some of the pitfalls mentioned above. This year, under the direction of Stuart Kim, the course again gave students the option to get genotyped (with a choice between services provided by 23andme or Lumigenix) and those students were free to explore the interpretations offered by the companies. However, they also re-interpreted their genotypes every week, by following along in lectures given by experts in each field. For instance, while Euan Ashley spoke about Coronary Artery Disease, students would look up (possibly imputing) their genotypes at the loci discussed. For this reason, the other TAs (Nick Tatonetti and Rob Tirrell) and I, with the help of Pablo Cordero implemented the Interpretome. In this Javascript and HTML5 system, all analysis of genotypes is done inside the browser, allowing for completely private interpretation of your genome. Each lecture was accompanied by an exercise; for example, students could follow along and calculate their optimal starting warfarin dose based on clinical and genetic factors as Russ Altman spoke about pharmacogenomics. The students could then optionally and anonymously submit their genotypes to the server, where we aggregated results and displayed allele class frequencies in real time.

The site provides an open-source framework for personal genome interpretation, demonstrating the power of genotyping for ancestral and clinical analysis (though it should be noted that this service, like 23andme, should not be used for diagnostic purposes and is not approved by the FDA). We also feature an exploratory section, mirroring the lectures of the course, as well as other analyses of interest and an option to upload your own analyses. In here, you’ll find the fun Neandertal calculator, to calculate your number of alleles likely derived from Neandertal (according to Green et al.).

As new results like this one pop up, this open framework will allow users to customize their analyses based on their interest. Explore your genome at www.interpretome.com.


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  • Improving genetic diagnosis in Mendelian disease with transcriptome sequencing. Cummings BB, Marshall JL, Tukiainen T, Lek M, Donkervoort S, Foley AR, Bolduc V, Waddell LB, Sandaradura SA, O'Grady GL, Estrella E, Reddy HM, Zhao F, Weisburd B, Karczewski KJ, O'Donnell-Luria AH, Birnbaum D, Sarkozy A, Hu Y, Gonorazky H, Claeys K, Joshi H, Bournazos A, Oates EC, Ghaoui R, Davis MR, Laing NG, Topf A, Genotype-Tissue Expression Consortium, Kang PB, Beggs AH, North KN, Straub V, Dowling JJ, Muntoni F, Clarke NF, Cooper ST, Bönnemann CG, MacArthur DG


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