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dc.contributor.authorFarooq, Amna
dc.contributor.authorGrønmyr, Sindre
dc.contributor.authorOmer, Ali Avan
dc.contributor.authorRognes, Torbjørn
dc.contributor.authorScheffler, Katja
dc.contributor.authorBjørås, Magnar
dc.contributor.authorWang, Junbai
dc.date.accessioned2021-01-08T08:43:08Z
dc.date.available2021-01-08T08:43:08Z
dc.date.created2020-11-10T00:16:01Z
dc.date.issued2020
dc.identifier.citationComputational and Structural Biotechnology Journal. 2020, 18 2877-2889.en_US
dc.identifier.issn2001-0370
dc.identifier.urihttps://hdl.handle.net/11250/2722131
dc.description.abstractDNA methylation (5mC) and hydroxymethylation (5hmC) are chemical modifications of cytosine bases which play a crucial role in epigenetic gene regulation. However, cost, data complexity and unavailability of comprehensive analytical tools is one of the major challenges in exploring these epigenetic marks. Hydroxymethylation-and Methylation-Sensitive Tag sequencing (HMST-seq) is one of the most costeffective techniques that enables simultaneous detection of 5mC and 5hmC at single base pair resolution. We present HMST-Seq-Analyzer as a comprehensive and robust method for performing simultaneous differential methylation analysis on 5mC and 5hmC data sets. HMST-Seq-Analyzer can detect Differentially Methylated Regions (DMRs), annotate them, give a visual overview of methylation status and also perform preliminary quality check on the data. In addition to HMST-Seq, our tool can be used on wholegenome bisulfite sequencing (WGBS) and reduced representation bisulfite sequencing (RRBS) data sets as well. The tool is written in Python with capacity to process data in parallel and is available at (https://hmst-seq.github.io/hmst/)en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleHMST-Seq-Analyzer: A new python tool for differential methylation and hydroxymethylation analysis in various DNA methylation sequencing dataen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber2877-2889en_US
dc.source.volume18en_US
dc.source.journalComputational and Structural Biotechnology Journalen_US
dc.identifier.doi10.1016/j.csbj.2020.09.038
dc.identifier.cristin1846368
dc.relation.projectNotur/NorStore: nn4605ken_US
dc.relation.projectHelse Sør-Øst RHF: HSØ 2018107en_US
dc.relation.projectHelse Sør-Øst RHF: HSØ 2017061en_US
dc.description.localcode© 2020 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY license (http://creativecommons. org/licenses/by/4.0/).en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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