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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.
SUBMITTER: Kwon M
PROVIDER: S-EPMC8055225 | biostudies-literature | 2021 Apr
REPOSITORIES: biostudies-literature
Kwon Minseok M Lee Soohyun S Berselli Michele M Chu Chong C Park Peter J PJ
Bioinformatics (Oxford, England) 20210401 2
<h4>Summary</h4>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 ...[more]