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CaReAl: capturing read alignments in a BAM file rapidly and conveniently

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Authors
Park, Yoomi; Seo, Heewon; Yoo, Kyunghun; Kim, Ju Han
Issue Date
2021-01-26
Publisher
Springer Open
Citation
Journal of Big Data. 2021 Jan 26;8(1):23
Keywords
High‐throughput sequencingData visualizationVariant evaluation
Abstract
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.
ISSN
2196-1115
Language
English
URI
https://hdl.handle.net/10371/173895
DOI
https://doi.org/10.1186/s40537-021-00418-w
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College of Medicine/School of Medicine (의과대학/대학원)Biomedical Engineering (의공학전공)Journal Papers (저널논문_의공학전공)
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