Identification of large-scale genomic variation in cancer genomes using in silico reference models.

ABSTRACT: Identifying large-scale structural variation in cancer genomes continues to be a challenge to researchers. Current methods rely on genome alignments based on a reference that can be a poor fit to highly variant and complex tumor genomes. To address this challenge we developed a method that uses available breakpoint information to generate models of structural variations. We use these models as references to align previously unmapped and discordant reads from a genome. By using these models to align unmapped reads, we show that our method can help to identify large-scale variations that have been previously missed.

SUBMITTER: Killcoyne S 

PROVIDER: S-EPMC4705683 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature