A spectral approach integrating functional genomic annotations for coding and noncoding variants.

ABSTRACT: Over the past few years, substantial effort has been put into the functional annotation of variation in human genome sequences. Such annotations can have a critical role in identifying putatively causal variants for a disease or trait among the abundant natural variation that occurs at a locus of interest. The main challenges in using these various annotations include their large numbers and their diversity. Here we develop an unsupervised approach to integrate these different annotations into one measure of functional importance (Eigen) that, unlike most existing methods, is not based on any labeled training data. We show that the resulting meta-score has better discriminatory ability using disease-associated and putatively benign variants from published studies (in both coding and noncod

SUBMITTER: Ionita-Laza I 

PROVIDER: S-EPMC4731313 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature