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dc.contributor.authorDisney-Hogg, L
dc.contributor.authorKinnersley, B
dc.contributor.authorHoulston, R
dc.date.accessioned2023-08-01T14:12:51Z
dc.date.available2023-08-01T14:12:51Z
dc.date.issued2020-01-01
dc.identifier.citationWellcome Open Research, 2020, 5 pp. 289 -
dc.identifier.issn2398-502X
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/5906
dc.identifier.eissn2398-502X
dc.identifier.eissn2398-502X
dc.identifier.doi10.12688/wellcomeopenres.16394.2
dc.description.abstractChromosome conformation capture methodologies have provided insight into the effect of 3D genomic architecture on gene regulation. Capture Hi-C (CHi-C) is a recent extension of Hi-C that improves the effective resolution of chromatin interactions by enriching for defined regions of biological relevance. The varying targeting efficiency between capture regions, however, introduces bias not present in conventional Hi-C, making analysis more complicated. Here we consider salient features of an algorithm that should be considered in evaluating the performance of a program used to analyse CHi-C data in order to infer meaningful interactions. We use the program CHICAGO to analyse promoter capture Hi-C data generated on 28 different cell lines as a case study.
dc.formatElectronic-eCollection
dc.format.extent289 -
dc.languageeng
dc.language.isoeng
dc.relation.ispartofWellcome Open Research
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleAlgorithmic considerations when analysing capture Hi-C data.
dc.typeJournal Article
dcterms.dateAccepted2020-01-01
dc.date.updated2023-08-01T14:11:41Z
rioxxterms.versionVoR
rioxxterms.versionofrecord10.12688/wellcomeopenres.16394.2
rioxxterms.licenseref.startdate2020-01-01
rioxxterms.typeJournal Article/Review
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Genetics and Epidemiology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Genetics and Epidemiology/Cancer Genomics
pubs.publication-statusPublished
pubs.volume5
icr.researchteamCancer Genomics
dc.contributor.icrauthorKinnersley, Benjamin
dc.contributor.icrauthorHoulston, Richard
icr.provenanceDeposited by Mr Arek Surman (impersonating Prof Richard Houlston) on 2023-08-01. Deposit type is initial. No. of files: 1. Files: Algorithmic considerations when analysing capture Hi-C data.pdf


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