De novo ChIP-seq analysis

dc.citation.epage10en_US
dc.citation.issueNumber205en_US
dc.citation.spage1en_US
dc.citation.volumeNumber16en_US
dc.contributor.authorHe, X.en_US
dc.contributor.authorCicek, A. E.en_US
dc.contributor.authorWang, Y.en_US
dc.contributor.authorSchulz, M. H.en_US
dc.contributor.authorLe, Hai-Sonen_US
dc.contributor.authorBar-Joseph, Z.en_US
dc.date.accessioned2016-02-08T09:38:30Z
dc.date.available2016-02-08T09:38:30Z
dc.date.issued2015en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.description.abstractMethods for the analysis of chromatin immunoprecipitation sequencing (ChIP-seq) data start by aligning the short reads to a reference genome. While often successful, they are not appropriate for cases where a reference genome is not available. Here we develop methods for de novo analysis of ChIP-seq data. Our methods combine de novo assembly with statistical tests enabling motif discovery without the use of a reference genome. We validate the performance of our method using human and mouse data. Analysis of fly data indicates that our method outperforms alignment based methods that utilize closely related species.en_US
dc.identifier.doi10.1186/s13059-015-0756-4en_US
dc.identifier.eissn1474-760Xen_US
dc.identifier.issn1474-7596en_US
dc.identifier.urihttp://hdl.handle.net/11693/20948en_US
dc.language.isoEnglishen_US
dc.publisherBioMed Central Ltd.en_US
dc.relation.isversionofhttp://dx.doi.org/10.1186/s13059-015-0756-4en_US
dc.source.titleGenome Biology: biology for the post-genomic eraen_US
dc.subjectHide markov modelen_US
dc.subjectReference genomeen_US
dc.subjectPeak callingen_US
dc.subjectCorrect motifen_US
dc.subjectJaspar databaseen_US
dc.titleDe novo ChIP-seq analysisen_US
dc.typeArticleen_US

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