Kwon Minseok, Lee Soohyun, Berselli Michele, Chu Chong, Park Peter J
Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA.
Bioinformatics. 2021 Apr 19;37(2):263-264. doi: 10.1093/bioinformatics/btaa1101.
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.
BamSnap is freely available at https://github.com/parklab/bamsnap.
Supplementary data are available at Bioinformatics online.
尽管变异检测算法有所改进，但在基因组分析中，对读取水平数据进行目视检查仍然是准确识别变异的关键步骤。我们开发了BamSnap，这是一种利用图形库和BAM索引的高效BAM文件查看器。与现有查看器不同，BamSnap可以快速生成高质量的快照，并具有定制的轨迹和布局。例如，我们为超过2500个全基因组在1000个基因组位点生成了读取水平的图像。
BamSnap可在https://github.com/parklab/bamsnap上免费获取。
补充数据可在《生物信息学》在线版获取。
