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dc.contributor.authorLavrichenko, Ksenia
dc.contributor.authorHelgeland, Øyvind
dc.contributor.authorNjølstad, Pål Rasmus
dc.contributor.authorJonassen, Inge
dc.contributor.authorJohansson, Stefan
dc.date.accessioned2022-02-03T14:10:13Z
dc.date.available2022-02-03T14:10:13Z
dc.date.created2021-08-25T09:22:02Z
dc.date.issued2021
dc.identifier.issn1367-4803
dc.identifier.urihttps://hdl.handle.net/11250/2976953
dc.description.abstractMotivation Single nucleotide polymorphism (SNP) genotyping arrays remain an attractive platform for assaying copy number variants (CNVs) in large population-wide cohorts. However, current tools for calling CNVs are still prone to extensive false positive calls when applied to biobank scale arrays. Moreover, there is a lack of methods exploiting cohorts with trios available (e.g. nuclear family) to assist in quality control and downstream analyses following the calling. Results We developed SeeCiTe (Seeing CNVs in Trios), a novel CNV-quality control tool that postprocesses output from current CNV-calling tools exploiting child-parent trio data to classify calls in quality categories and provide a set of visualizations for each putative CNV call in the offspring. We apply it to the Norwegian Mother, Father and Child Cohort Study (MoBa) and show that SeeCiTe improves the specificity and sensitivity compared to the common empiric filtering strategies. To our knowledge, it is the first tool that utilizes probe-level CNV data in trios (and singletons) to systematically highlight potential artifacts and visualize signal intensities in a streamlined fashion suitable for biobank scale studies.en_US
dc.language.isoengen_US
dc.publisherOxford University Pressen_US
dc.rightsNavngivelse-Ikkekommersiell 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/deed.no*
dc.titleSeeCiTe: a method to assess CNV calls from SNP arrays using trio dataen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersionen_US
dc.rights.holderCopyright The Author(s) 2021en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2
dc.identifier.doi10.1093/bioinformatics/btab028
dc.identifier.cristin1928554
dc.source.journalBioinformaticsen_US
dc.source.pagenumber1876-1883en_US
dc.relation.projectNorges forskningsråd: 229624en_US
dc.relation.projectNorges forskningsråd: 240413en_US
dc.relation.projectERC-European Research Council: 293574en_US
dc.relation.projectNovo Nordisk Fonden: NNF19OC0054741en_US
dc.relation.projectNovo Nordisk Fonden: NNF19OC0057445en_US
dc.relation.projectHelse Vest RHF: F-12144en_US
dc.relation.projectHelse Vest RHF: F-11528en_US
dc.identifier.citationBioinformatics. 2021, 37 (13), 1876-1883.en_US
dc.source.volume37en_US
dc.source.issue13en_US


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Navngivelse-Ikkekommersiell 4.0 Internasjonal
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