Recalibration of mapping quality scores in Illumina short-read alignments improves SNP detection results in low-coverage sequencing data.

ABSTRACT:

Background

Low-coverage sequencing is a cost-effective way to obtain reads spanning an entire genome. However, read depth at each locus is low, making sequencing error difficult to separate from actual variation. Prior to variant calling, sequencer reads are aligned to a reference genome, with alignments stored in Sequence Alignment/Map (SAM) files. Each alignment has a mapping quality (MAPQ) score indicating the probability a read is incorrectly aligned. This study investigated the recalibration of probability estimates used to compute MAPQ scores for improving variant calling performance in single-sample, low-coverage settings.

Materials and methods

Simulated tomato, hot pepper and rice genomes were implanted with known variants. From these, simulated paired-end reads were

SUBMITTER: Cline E 

PROVIDER: S-EPMC7727374 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature