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CaReAl: capturing read alignments in a BAM file rapidly and conveniently
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, Yoomi | - |
dc.contributor.author | Seo, Heewon | - |
dc.contributor.author | Yoo, Kyunghun | - |
dc.contributor.author | Kim, Ju Han | - |
dc.date.accessioned | 2021-03-23T06:48:45Z | - |
dc.date.available | 2021-03-23T16:00:30Z | - |
dc.date.issued | 2021-01-26 | - |
dc.identifier.citation | Journal of Big Data. 2021 Jan 26;8(1):23 | ko_KR |
dc.identifier.issn | 2196-1115 | - |
dc.identifier.uri | https://hdl.handle.net/10371/173895 | - |
dc.description.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. | ko_KR |
dc.description.sponsorship | This research was supported by a Grant (16183MFDS541) from the Ministry of Food and Drug Safety in 2019. | ko_KR |
dc.language.iso | en | ko_KR |
dc.publisher | Springer Open | ko_KR |
dc.subject | High‐throughput sequencing | - |
dc.subject | Data visualization | - |
dc.subject | Variant evaluation | - |
dc.title | CaReAl: capturing read alignments in a BAM file rapidly and conveniently | ko_KR |
dc.type | Article | ko_KR |
dc.contributor.AlternativeAuthor | 박유미 | - |
dc.contributor.AlternativeAuthor | 서희원 | - |
dc.contributor.AlternativeAuthor | 유경훈 | - |
dc.contributor.AlternativeAuthor | 김주한 | - |
dc.identifier.doi | 10.1186/s40537-021-00418-w | - |
dc.citation.journaltitle | Journal of Big Data | ko_KR |
dc.language.rfc3066 | en | - |
dc.rights.holder | The Author(s) | - |
dc.date.updated | 2021-01-27T10:47:11Z | - |
dc.citation.number | 1 | ko_KR |
dc.citation.startpage | 23 | ko_KR |
dc.citation.volume | 8 | ko_KR |
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