Genomic Feature Selection by Coverage Design Optimization.

ABSTRACT: We introduce a novel data reduction technique whereby we select a subset of tiles to "cover" maximally events of interest in large-scale biological datasets (e.g., genetic mutations), while minimizing the number of tiles. A tile is a genomic unit capturing one or more biological events, such as a sequence of base pairs that can be sequenced and observed simultaneously. The goal is to reduce significantly the number of tiles considered to those with areas of dense events in a cohort, thus saving on cost and enhancing interpretability. However, the reduction should not come at the cost of too much information, allowing for sensible statistical analysis after its application. We envisage application of our methods to a variety of high throughput data types, particularly those produced by next

SUBMITTER: Reid S 

PROVIDER: S-EPMC6173524 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature