BreaKmer: detection of structural variation in targeted massively parallel sequencing data using kmers.

ABSTRACT: Genomic structural variation (SV), a common hallmark of cancer, has important predictive and therapeutic implications. However, accurately detecting SV using high-throughput sequencing data remains challenging, especially for 'targeted' resequencing efforts. This is critically important in the clinical setting where targeted resequencing is frequently being applied to rapidly assess clinically actionable mutations in tumor biopsies in a cost-effective manner. We present BreaKmer, a novel approach that uses a 'kmer' strategy to assemble misaligned sequence reads for predicting insertions, deletions, inversions, tandem duplications and translocations at base-pair resolution in targeted resequencing data. Variants are predicted by realigning an assembled consensus sequence created from sequen

SUBMITTER: Abo RP 

PROVIDER: S-EPMC4330340 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature