BamSnap: a lightweight viewer for sequencing reads in BAM files

Minseok Kwon; Soohyun Lee; Michele Berselli; Chong Chu; Peter J Park

doi:10.1093/bioinformatics/btaa1101

BamSnap: a lightweight viewer for sequencing reads in BAM files

Bioinformatics. 2021 Apr 19;37(2):263-264. doi: 10.1093/bioinformatics/btaa1101.

Authors

Minseok Kwon¹, Soohyun Lee¹, Michele Berselli¹, Chong Chu¹, Peter J Park¹

Affiliation

¹ Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA.

Abstract

Summary: Despite the improvement in variant detection algorithms, visual inspection of the read-level data remains an essential step for accurate identification of variants in genome analysis. We developed BamSnap, an efficient BAM file viewer utilizing a graphics library and BAM indexing. In contrast to existing viewers, BamSnap can generate high-quality snapshots rapidly, with customized tracks and layout. As an example, we produced read-level images at 1000 genomic loci for >2500 whole-genomes.

Availability and implementation: BamSnap is freely available at https://github.com/parklab/bamsnap.

Supplementary information: Supplementary data are available at Bioinformatics online.

Abstract

Grants and funding