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

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dc.contributor.authorPark, Yoomi-
dc.contributor.authorSeo, Heewon-
dc.contributor.authorYoo, Kyunghun-
dc.contributor.authorKim, Ju Han-
dc.date.accessioned2021-03-23T06:48:45Z-
dc.date.available2021-03-23T16:00:30Z-
dc.date.issued2021-01-26-
dc.identifier.citationJournal of Big Data. 2021 Jan 26;8(1):23ko_KR
dc.identifier.issn2196-1115-
dc.identifier.urihttps://hdl.handle.net/10371/173895-
dc.description.abstractSome 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.ko_KR
dc.description.sponsorshipThis research was supported by a Grant (16183MFDS541) from the Ministry of Food and Drug Safety in 2019.ko_KR
dc.language.isoenko_KR
dc.publisherSpringer Openko_KR
dc.subjectHigh‐throughput sequencing-
dc.subjectData visualization-
dc.subjectVariant evaluation-
dc.titleCaReAl: capturing read alignments in a BAM file rapidly and convenientlyko_KR
dc.typeArticleko_KR
dc.contributor.AlternativeAuthor박유미-
dc.contributor.AlternativeAuthor서희원-
dc.contributor.AlternativeAuthor유경훈-
dc.contributor.AlternativeAuthor김주한-
dc.identifier.doi10.1186/s40537-021-00418-w-
dc.citation.journaltitleJournal of Big Datako_KR
dc.language.rfc3066en-
dc.rights.holderThe Author(s)-
dc.date.updated2021-01-27T10:47:11Z-
dc.citation.number1ko_KR
dc.citation.startpage23ko_KR
dc.citation.volume8ko_KR
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