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Cloud-BS: A MapReduce-based bisulfite sequencing aligner on cloud

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dc.contributor.authorChoi, Joungmin-
dc.contributor.authorPark, Yoonjae-
dc.contributor.authorKim, Sun-
dc.contributor.authorChae, Heejoon-
dc.date.available2021-02-22T07:46:20Z-
dc.date.created2020-08-18-
dc.date.issued2018-12-
dc.identifier.issn0219-7200-
dc.identifier.urihttps://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/4146-
dc.description.abstractIn recent years, there have been many studies utilizing DNA methylome data to answer fundamental biological questions. Bisulfite sequencing (BS-seq) has enabled measurement of a genome-wide absolute level of DNA methylation at single-nucleotide resolution. However, due to the ambiguity introduced by bisulfite-treatment, the aligning process especially in large-scale epigenetic research is still considered a huge burden. We present Cloud-BS, an efficient BS-seq aligner designed for parallel execution on a distributed environment. Utilizing Apache Hadoop framework, Cloud-BS splits sequencing reads into multiple blocks and transfers them to distributed nodes. By designing each aligning procedure into separate map and reducing tasks while an internal key-value structure is optimized based on the MapReduce programming model, the algorithm significantly improves alignment performance without sacrificing mapping accuracy. In addition, Cloud-BS minimizes the innate burden of configuring a distributed environment by providing a pre-configured cloud image. Cloud-BS shows significantly improved bisulfite alignment performance compared to other existing BS-seq aligners. We believe our algorithm facilitates large-scale methylome data analysis. The algorithm is freely available at https://paryoja.github.io/Cloud-BS/.-
dc.language영어-
dc.language.isoen-
dc.publisherIMPERIAL COLLEGE PRESS-
dc.titleCloud-BS: A MapReduce-based bisulfite sequencing aligner on cloud-
dc.typeArticle-
dc.contributor.affiliatedAuthorChae, Heejoon-
dc.identifier.doi10.1142/S0219720018400280-
dc.identifier.scopusid2-s2.0-85058816434-
dc.identifier.wosid000455392200007-
dc.identifier.bibliographicCitationJOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY, v.16, no.6-
dc.relation.isPartOfJOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY-
dc.citation.titleJOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY-
dc.citation.volume16-
dc.citation.number6-
dc.type.rimsART-
dc.type.docTypeArticle; Proceedings Paper-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaBiochemistry & Molecular Biology-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaMathematical & Computational Biology-
dc.relation.journalWebOfScienceCategoryBiochemical Research Methods-
dc.relation.journalWebOfScienceCategoryComputer Science, Interdisciplinary Applications-
dc.relation.journalWebOfScienceCategoryMathematical & Computational Biology-
dc.subject.keywordPlusDNA METHYLATION-
dc.subject.keywordPlusPIPELINE-
dc.subject.keywordPlusALIGNMENT-
dc.subject.keywordPlusSOFTWARE-
dc.subject.keywordPlusCANCER-
dc.subject.keywordAuthorBisulfite sequencing-
dc.subject.keywordAuthoraligner-
dc.subject.keywordAuthordistributed-
dc.subject.keywordAuthorMapReduce-
dc.subject.keywordAuthorcloud-
dc.identifier.urlhttps://www.worldscientific.com/doi/abs/10.1142/S0219720018400280-
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