Written by: Stephen Hsu
Primary Source: Information Processing
I’m in Mountain View to give a talk at 23andMe. Their latest funding round was $250M on a (reported) valuation of $1.5B. If I just add up the Crunchbase numbers it looks like almost half a billion invested at this point…
Abstract: We apply methods from Compressed Sensing (L1-penalized regression; Donoho-Tanner phase transition with noise) to the UKBB dataset of 500k SNP genotypes. We construct genomic predictors for several complex traits. Our height predictor captures nearly all of the predicted SNP heritability for this trait — thereby resolving the missing heritability problem. Actual heights of most individuals in validation tests are within a few cm of predicted heights. I also discuss application of these methods to polygenic disease risk: sparsity estimates (of the number of causal loci), combined with phase transition scaling analysis, allow estimates of the amount of case | control data required to construct good predictors.
Here’s how people + robots handle your spit sample to produce a SNP genotype: