BACOM2.0 facilitates absolute normalization and quantification of somatic copy number alterations in heterogeneous tumor

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dc.contributor.authorFu, Yien
dc.contributor.authorYu, Guoqiangen
dc.contributor.authorLevine, Douglas A.en
dc.contributor.authorWang, Niyaen
dc.contributor.authorShih, Ie-Mingen
dc.contributor.authorZhang, Zhenen
dc.contributor.authorClarke, Roberten
dc.contributor.authorWang, Yueen
dc.contributor.departmentElectrical and Computer Engineeringen
dc.date.accessioned2019-01-24T18:24:47Zen
dc.date.available2019-01-24T18:24:47Zen
dc.date.issued2015-09-09en
dc.description.abstractMost published copy number datasets on solid tumors were obtained from specimens comprised of mixed cell populations, for which the varying tumor-stroma proportions are unknown or unreported. The inability to correct for signal mixing represents a major limitation on the use of these datasets for subsequent analyses, such as discerning deletion types or detecting driver aberrations. We describe the BACOM2.0 method with enhanced accuracy and functionality to normalize copy number signals, detect deletion types, estimate tumor purity, quantify true copy numbers, and calculate average-ploidy value. While BACOM has been validated and used with promising results, subsequent BACOM analysis of the TCGA ovarian cancer dataset found that the estimated average tumor purity was lower than expected. In this report, we first show that this lowered estimate of tumor purity is the combined result of imprecise signal normalization and parameter estimation. Then, we describe effective allele-specific absolute normalization and quantification methods that can enhance BACOM applications in many biological contexts while in the presence of various confounders. Finally, we discuss the advantages of BACOM in relation to alternative approaches. Here we detail this revised computational approach, BACOM2.0, and validate its performance in real and simulated datasets.en
dc.description.notesThis work was supported in part by the National Institutes of Health under Grants CA149653, CA160036, HL111362, CA184902, NS029525, and ES024988.en
dc.description.sponsorshipNational Institutes of Health [CA149653, CA160036, HL111362, CA184902, NS029525, ES024988]en
dc.format.extent11en
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1038/srep13955en
dc.identifier.issn2045-2322en
dc.identifier.other13955en
dc.identifier.pmid26350498en
dc.identifier.urihttp://hdl.handle.net/10919/86882en
dc.identifier.volume5en
dc.language.isoenen
dc.publisherSpringer Natureen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectinformation-theoretic criteriaen
dc.subjectgeneration sequencing dataen
dc.subjectsignificant aberrationsen
dc.subjectcanceren
dc.subjectsamplesen
dc.subjectidentificationen
dc.subjectgenomeen
dc.subjectpurityen
dc.subjectaneuploidyen
dc.subjectcarcinomaen
dc.titleBACOM2.0 facilitates absolute normalization and quantification of somatic copy number alterations in heterogeneous tumoren
dc.title.serialScientific Reportsen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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