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dc.contributor.authorHe, Xin
dc.contributor.authorCicek, A. Ercument
dc.contributor.authorWang, Yuhao
dc.contributor.authorSchulz, Marcel H.
dc.contributor.authorLe, Hai-Son
dc.contributor.authorBar-Joseph, Ziv
dc.date.accessioned2015-09-24T17:52:22Z
dc.date.available2015-09-24T17:52:22Z
dc.date.issued2015-09
dc.date.submitted2015-06
dc.identifier.issn1474-760X
dc.identifier.urihttp://hdl.handle.net/1721.1/98902
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.publisherBioMed Centralen_US
dc.relation.isversionofhttp://dx.doi.org/10.1186/s13059-015-0756-4en_US
dc.titleDe novo ChIP-seq analysisen_US
dc.typeArticleen_US
dc.identifier.citationHe, Xin, A. Ercument Cicek, Yuhao Wang, Marcel H. Schulz, Hai-Son Le, and Ziv Bar-Joseph. "De novo ChIP-seq analysis." Genome Biology. 2015 Sep 23;16(1):205.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.mitauthorWang, Yuhaoen_US
dc.relation.journalGenome Biologyen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2015-09-24T03:41:56Z
dc.language.rfc3066en
dc.rights.holderHe et al.
dspace.orderedauthorsHe, Xin; Cicek, A. Ercument; Wang, Yuhao; Schulz, Marcel H.; Le, Hai-Son; Bar-Joseph, Ziven_US
dc.identifier.orcidhttps://orcid.org/0000-0002-3430-6943
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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