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

16 Mar 2013  ·  Heng Li ·

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

PDF Abstract

Datasets


  Add Datasets introduced or used in this paper

Results from the Paper


Task Dataset Model Metric Name Metric Value Global Rank Uses Extra
Training Data
Benchmark
3D Object Reconstruction From A Single Image RenderPeople ali Point-to-surface distance (cm) 002 # 3
Chamfer (cm) 202 # 4
Surface normal consistency 0.2 # 3

Methods


No methods listed for this paper. Add relevant methods here