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dc.contributor.authorFan, Xian
Zhou, Wanding
Chong, Zechen
Nakhleh, Luay
Chen, Ken
dc.date.accessioned 2014-10-30T19:33:32Z
dc.date.available 2014-10-30T19:33:32Z
dc.date.issued 2014
dc.identifier.citation Fan, Xian, Zhou, Wanding, Chong, Zechen, et al.. "Towards accurate characterization of clonal heterogeneity based on structural variation." BMC Bioinformatics, 15, (2014) BioMed Central: 299. http://dx.doi.org/10.1186/1471-2105-15-299.
dc.identifier.urihttps://hdl.handle.net/1911/77673
dc.description.abstract Recent advances in deep digital sequencing have unveiled an unprecedented degree of clonal heterogeneity within a single tumor DNA sample. Resolving such heterogeneity depends on accurate estimation of fractions of alleles that harbor somatic mutations. Unlike substitutions or small indels, structural variants such as deletions, duplications, inversions and translocations involve segments of DNAs and are potentially more accurate for allele fraction estimations. However, no systematic method exists that can support such analysis. In this paper, we present a novel maximum-likelihood method that estimates allele fractions of structural variants integratively from various forms of alignment signals. We develop a tool, BreakDown, to estimate the allele fractions of most structural variants including medium size (from 1 kilobase to 1 megabase) deletions and duplications, and balanced inversions and translocations. Evaluation based on both simulated and real data indicates that our method systematically enables structural variants for clonal heterogeneity analysis and can greatly enhance the characterization of genomically instable tumors.
dc.language.iso eng
dc.publisher BioMed Central
dc.rightsThis article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.title Towards accurate characterization of clonal heterogeneity based on structural variation
dc.type Journal article
dc.contributor.funder National Cancer Institute
dc.contributor.funder National Human Genome Research Institute
dc.citation.journalTitle BMC Bioinformatics
dc.subject.keywordstructural variation
clonal heterogeneity
variant allele fraction
dc.citation.volumeNumber 15
dc.type.dcmi Text
dc.identifier.doihttp://dx.doi.org/10.1186/1471-2105-15-299
dc.identifier.pmcid PMC4165998
dc.identifier.pmid 25201439
dc.identifier.grantID R01-CA172652 (National Cancer Institute)
dc.identifier.grantID U41-HG007497-01 (National Human Genome Research Institute)
dc.identifier.grantID P30-CA016672 (National Cancer Institute)
dc.type.publication publisher version
dc.citation.firstpage 299


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This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Except where otherwise noted, this item's license is described as This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.