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Article: CNGPLD: case-control copy-number analysis using Gaussian process latent difference

TitleCNGPLD: case-control copy-number analysis using Gaussian process latent difference
Authors
Issue Date2022
Citation
Bioinformatics, 2022, v. 38, n. 8, p. 2096-2101 How to Cite?
AbstractMotivation: Cross-sectional analyses of primary cancer genomes have identified regions of recurrent somatic copy-number alteration, many of which result from positive selection during cancer formation and contain driver genes. However, no effective approach exists for identifying genomic loci under significantly different degrees of selection in cancers of different subtypes, anatomic sites or disease stages. Results: CNGPLD is a new tool for performing case-control somatic copy-number analysis that facilitates the discovery of differentially amplified or deleted copy-number aberrations in a case group of cancer compared with a control group of cancer. This tool uses a Gaussian process statistical framework in order to account for the covariance structure of copy-number data along genomic coordinates and to control the false discovery rate at the region level.
Persistent Identifierhttp://hdl.handle.net/10722/313945
ISSN
2023 Impact Factor: 4.4
2023 SCImago Journal Rankings: 2.574
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorShih, David J.H.-
dc.contributor.authorLi, Ruoxing-
dc.contributor.authorMüller, Peter-
dc.contributor.authorZheng, W. Jim-
dc.contributor.authorDo, Kim Anh-
dc.contributor.authorLin, Shiaw Yih-
dc.contributor.authorCarter, Scott L.-
dc.date.accessioned2022-07-06T11:28:33Z-
dc.date.available2022-07-06T11:28:33Z-
dc.date.issued2022-
dc.identifier.citationBioinformatics, 2022, v. 38, n. 8, p. 2096-2101-
dc.identifier.issn1367-4803-
dc.identifier.urihttp://hdl.handle.net/10722/313945-
dc.description.abstractMotivation: Cross-sectional analyses of primary cancer genomes have identified regions of recurrent somatic copy-number alteration, many of which result from positive selection during cancer formation and contain driver genes. However, no effective approach exists for identifying genomic loci under significantly different degrees of selection in cancers of different subtypes, anatomic sites or disease stages. Results: CNGPLD is a new tool for performing case-control somatic copy-number analysis that facilitates the discovery of differentially amplified or deleted copy-number aberrations in a case group of cancer compared with a control group of cancer. This tool uses a Gaussian process statistical framework in order to account for the covariance structure of copy-number data along genomic coordinates and to control the false discovery rate at the region level.-
dc.languageeng-
dc.relation.ispartofBioinformatics-
dc.titleCNGPLD: case-control copy-number analysis using Gaussian process latent difference-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1093/bioinformatics/btac096-
dc.identifier.scopuseid_2-s2.0-85128732626-
dc.identifier.volume38-
dc.identifier.issue8-
dc.identifier.spage2096-
dc.identifier.epage2101-
dc.identifier.eissn1460-2059-
dc.identifier.isiWOS:000761594400001-

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