| Literature DB >> 33416869 |
Minseok Kwon1, Soohyun Lee1, Michele Berselli1, Chong Chu1, Peter J Park1.
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: BamSnap is freely available at https://github.com/parklab/bamsnap. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.Entities:
Year: 2021 PMID: 33416869 PMCID: PMC8055225 DOI: 10.1093/bioinformatics/btaa1101
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937