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dc.contributor.authorDing, Qiliang
dc.contributor.authorSomerville, Cherith
dc.contributor.authorManshaei, Roozbeh
dc.contributor.authorTrost, Brett
dc.contributor.authorReuter, Miriam S.
dc.contributor.authorKalbfleisch, Kelsey
dc.contributor.authorStanley, Kaitlin
dc.contributor.authorOkello, John B. A.
dc.contributor.authorHosseini, S. M.
dc.contributor.authorListon, Eriskay
dc.contributor.authorCurtis, Meredith
dc.contributor.authorZarrei, Mehdi
dc.contributor.authorHigginbotham, Edward J.
dc.contributor.authorChan, Ada J. S.
dc.contributor.authorEngchuan, Worrawat
dc.contributor.authorThiruvahindrapuram, Bhooma
dc.contributor.authorScherer, Stephen W.
dc.contributor.authorKim, Raymond H.
dc.contributor.authorJobling, Rebekah K.
dc.date.accessioned2022-11-21T14:05:51Z
dc.date.available2022-11-21T14:05:51Z
dc.date.issued2022-11-14
dc.identifier.urihttps://hdl.handle.net/1721.1/146556
dc.description.abstractAbstract Copy number variants (CNVs) represent major etiologic factors in rare genetic diseases. Current clinical CNV interpretation workflows require extensive back-and-forth with multiple tools and databases. This increases complexity and time burden, potentially resulting in missed genetic diagnoses. We present the Suite for CNV Interpretation and Prioritization (SCIP), a software package for the clinical interpretation of CNVs detected by whole-genome sequencing (WGS). The SCIP Visualization Module near-instantaneously displays all information necessary for CNV interpretation (variant quality, population frequency, inheritance pattern, and clinical relevance) on a single page—supported by modules providing variant filtration and prioritization. SCIP was comprehensively evaluated using WGS data from 1027 families with congenital cardiac disease and/or autism spectrum disorder, containing 187 pathogenic or likely pathogenic (P/LP) CNVs identified in previous curations. SCIP was efficient in filtration and prioritization: a median of just two CNVs per case were selected for review, yet it captured all P/LP findings (92.5% of which ranked 1st). SCIP was also able to identify one pathogenic CNV previously missed. SCIP was benchmarked against AnnotSV and a spreadsheet-based manual workflow and performed superiorly than both. In conclusion, SCIP is a novel software package for efficient clinical CNV interpretation, substantially faster and more accurate than previous tools (available at https://github.com/qd29/SCIP , a video tutorial series is available at https://bit.ly/SCIPVideos ).en_US
dc.publisherSpringer Berlin Heidelbergen_US
dc.relation.isversionofhttps://doi.org/10.1007/s00439-022-02494-1en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceSpringer Berlin Heidelbergen_US
dc.titleSCIP: software for efficient clinical interpretation of copy number variants detected by whole-genome sequencingen_US
dc.typeArticleen_US
dc.identifier.citationDing, Qiliang, Somerville, Cherith, Manshaei, Roozbeh, Trost, Brett, Reuter, Miriam S. et al. 2022. "SCIP: software for efficient clinical interpretation of copy number variants detected by whole-genome sequencing."
dc.contributor.departmentSloan School of Management
dc.identifier.mitlicensePUBLISHER_CC
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.updated2022-11-20T04:16:51Z
dc.language.rfc3066en
dc.rights.holderThe Author(s)
dspace.embargo.termsN
dspace.date.submission2022-11-20T04:16:51Z
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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