S-Space College of Medicine/School of Medicine (의과대학/대학원) Biomedical Engineering (의공학전공) Journal Papers (저널논문_의공학전공)
CaReAl: capturing read alignments in a BAM file rapidly and conveniently
- Park, Yoomi; Seo, Heewon; Yoo, Kyunghun; Kim, Ju Han
- Issue Date
- Springer Open
- Journal of Big Data. 2021 Jan 26;8(1):23
- Some of the variants detected by high-throughput sequencing (HTS) are often not reproducible. To minimize the technical-induced artifacts, secondary experimental validation is required but this step is unnecessarily slow and expensive. Thus, developing a rapid and easy to use visualization tool is necessary to systematically review the statuses of sequence read alignments. Here, we developed a high-performance alignment capturing tool, CaReAl, for visualizing the read-alignment status of nucleotide sequences and associated genome features. CaReAl is optimized for the systematic exploration of regions of interest by visualizing full-depth read-alignment statuses in a set of PNG files. CaReAl was 7.5 times faster than IGV snapshot, the only stand-alone tool which provides an automated snapshot of sequence reads. This rapid user-programmable capturing tool is useful for obtaining read-level data for evaluating variant calls and detecting technical biases. The multithreading and sequential wide-genome-range-capturing functionalities of CaReAl aid the efficient manual review and evaluation of genome sequence alignments and variant calls. CaReAl is a rapid and convenient tool for capturing aligned reads in BAM. CaReAl facilitates the acquisition of highly curated data for obtaining reliable analytic results.