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dc.contributor.authorDavidson, NM
dc.contributor.authorOshlack, A
dc.date.accessioned2020-12-17T03:02:05Z
dc.date.available2020-12-17T03:02:05Z
dc.date.issued2014-01-01
dc.identifierpii: s13059-014-0410-6
dc.identifier.citationDavidson, N. M. & Oshlack, A. (2014). Corset: enabling differential gene expression analysis for de novo assembled transcriptomes. GENOME BIOLOGY, 15 (7), https://doi.org/10.1186/s13059-014-0410-6.
dc.identifier.issn1474-760X
dc.identifier.urihttp://hdl.handle.net/11343/254717
dc.description.abstractNext generation sequencing has made it possible to perform differential gene expression studies in non-model organisms. For these studies, the need for a reference genome is circumvented by performing de novo assembly on the RNA-seq data. However, transcriptome assembly produces a multitude of contigs, which must be clustered into genes prior to differential gene expression detection. Here we present Corset, a method that hierarchically clusters contigs using shared reads and expression, then summarizes read counts to clusters, ready for statistical testing. Using a range of metrics, we demonstrate that Corset out-performs alternative methods. Corset is available from https://code.google.com/p/corset-project/.
dc.languageEnglish
dc.publisherBMC
dc.titleCorset: enabling differential gene expression analysis for de novo assembled transcriptomes
dc.typeJournal Article
dc.identifier.doi10.1186/s13059-014-0410-6
melbourne.affiliation.departmentSchool of BioSciences
melbourne.affiliation.departmentSchool of Physics
melbourne.source.titleGenome Biology
melbourne.source.volume15
melbourne.source.issue7
dc.rights.licenseCC BY
melbourne.elementsid1222458
melbourne.contributor.authorDavidson, Nadia
melbourne.contributor.authorOshlack, Alicia
dc.identifier.eissn1474-760X
melbourne.accessrightsOpen Access


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