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dc.contributor.authorMarshall, Owen Jen
dc.contributor.authorBrand, Andreaen
dc.date.accessioned2015-07-01T13:36:10Z
dc.date.available2015-07-01T13:36:10Z
dc.date.issued2015-06-25en
dc.identifier.citationBioinformatics 2015, 31(20):3371-3373. doi:10.1093/bioinformatics/btv386en
dc.identifier.issn1367-4803
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/248778
dc.description.abstractSummary: DamID is a powerful technique for identifying regions of the genome bound by a DNA-binding (or DNA-associated) protein. Currently no method exists for automatically processing next-generation sequencing DamID (DamID-seq) data, and the use of DamID-seq datasets with normalisation based on read-counts alone can lead to high background and the loss of bound signal. DamID-seq thus presents novel challenges in terms of normalisation and background minimisation. We describe here damidseq_pipeline, a software pipeline that performs automatic normalisation and background reduction on multiple DamID-seq FASTQ datasets. Availability and implementation: Open-source and freely available from http://owenjm.github.io/damidseq_pipeline. The damidseq_pipeline is implemented in Perl and is compatible with any Unix-based operating system (e.g. Linux, Mac OSX).
dc.description.sponsorshipWe thank Charles Bradshaw for helpful comments on the software. This work was supported by the BBSRC [BB/L00786X/1] and Wellcome Trust [092545]. The Gurdon Institute is supported by core funding from the Wellcome Trust [092096] and CRUK [C6946/A14492].
dc.languageEnglishen
dc.language.isoenen
dc.publisherOxford Journals on behalf of the International Society for Computational Biology
dc.rightsAttribution 2.0 UK: England & Wales*
dc.rights.urihttp://creativecommons.org/licenses/by/2.0/uk/*
dc.titledamidseq pipeline: an automated pipeline for processing DamID sequencing datasetsen
dc.typeArticle
dc.description.versionThis is the final published version. It first appeared at http://dx.doi.org/10.1093/bioinformatics/btv386en
prism.endingPage3373
prism.publicationDate2015en
prism.publicationNameBioinformaticsen
prism.startingPage3371
prism.volume31en
dc.rioxxterms.funderBBSRC
dc.rioxxterms.funderWellcome Trust
dc.rioxxterms.funderCRUK
dc.rioxxterms.projectidBB/L00786X/1
dc.rioxxterms.projectid092545
dc.rioxxterms.projectid092096
dc.rioxxterms.projectidC6946/A14492
dcterms.dateAccepted2015-06-20en
rioxxterms.versionofrecord10.1093/bioinformatics/btv386en
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2015-06-25en
dc.contributor.orcidBrand, Andrea [0000-0002-2089-6954]
dc.identifier.eissn1367-4811
rioxxterms.typeJournal Article/Reviewen
pubs.funder-project-idBBSRC (BB/L00786X/1)
pubs.funder-project-idWellcome Trust (092545/Z/10/Z)
pubs.funder-project-idWellcome Trust (092096/Z/10/Z)
pubs.funder-project-idWELLCOME TRUST (103792/Z/14/Z)
pubs.funder-project-idCancer Research UK (A14492)


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Attribution 2.0 UK: England & Wales
Except where otherwise noted, this item's licence is described as Attribution 2.0 UK: England & Wales