Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM

TL;DR

BWA-MEM is a versatile and efficient alignment algorithm for mapping sequence reads and long sequences to large genomes, outperforming previous aligners in speed and accuracy, and supporting various sequencing technologies.

Contribution

It introduces BWA-MEM, a new alignment algorithm that automatically selects alignment modes, handles chimeric reads, and is robust across a wide range of sequence lengths.

Findings

BWA-MEM outperforms existing aligners for 100bp reads.

Supports long sequences up to several megabases.

Robust to sequencing errors and chimeric reads.

Abstract

Summary: BWA-MEM is a new alignment algorithm for aligning sequence reads or long query sequences against a large reference genome such as human. It automatically chooses between local and end-to-end alignments, supports paired-end reads and performs chimeric alignment. The algorithm is robust to sequencing errors and applicable to a wide range of sequence lengths from 70bp to a few megabases. For mapping 100bp sequences, BWA-MEM shows better performance than several state-of-art read aligners to date. Availability and implementation: BWA-MEM is implemented as a component of BWA, which is available at http://github.com/lh3/bwa. Contact: hengli@broadinstitute.org