Vargas: heuristic-free alignment for assessing linear and graph read aligners.

ABSTRACT:

Motivation

Read alignment is central to many aspects of modern genomics. Most aligners use heuristics to accelerate processing, but these heuristics can fail to find the optimal alignments of reads. Alignment accuracy is typically measured through simulated reads; however, the simulated location may not be the (only) location with the optimal alignment score.

Results

Vargas implements a heuristic-free algorithm guaranteed to find the highest-scoring alignment for real sequencing reads to a linear or graph genome. With semiglobal and local alignment modes and affine gap and quality-scaled mismatch penalties, it can implement the scoring functions of commonly used aligners to calculate optimal alignments. While this is computationally intensive, Vargas uses multi-core parallel

SUBMITTER: Darby CA 

PROVIDER: S-EPMC7320598 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature