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

Most 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 su...

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Autores principales: Fu, Yi, Yu, Guoqiang, Levine, Douglas A., Wang, Niya, Shih, Ie-Ming, Zhang, Zhen, Clarke, Robert, Wang, Yue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4563570/
https://www.ncbi.nlm.nih.gov/pubmed/26350498
http://dx.doi.org/10.1038/srep13955
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author Fu, Yi
Yu, Guoqiang
Levine, Douglas A.
Wang, Niya
Shih, Ie-Ming
Zhang, Zhen
Clarke, Robert
Wang, Yue
author_facet Fu, Yi
Yu, Guoqiang
Levine, Douglas A.
Wang, Niya
Shih, Ie-Ming
Zhang, Zhen
Clarke, Robert
Wang, Yue
author_sort Fu, Yi
collection PubMed
description Most 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.
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spelling pubmed-45635702015-09-15 BACOM2.0 facilitates absolute normalization and quantification of somatic copy number alterations in heterogeneous tumor Fu, Yi Yu, Guoqiang Levine, Douglas A. Wang, Niya Shih, Ie-Ming Zhang, Zhen Clarke, Robert Wang, Yue Sci Rep Article Most 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. Nature Publishing Group 2015-09-09 /pmc/articles/PMC4563570/ /pubmed/26350498 http://dx.doi.org/10.1038/srep13955 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Fu, Yi
Yu, Guoqiang
Levine, Douglas A.
Wang, Niya
Shih, Ie-Ming
Zhang, Zhen
Clarke, Robert
Wang, Yue
BACOM2.0 facilitates absolute normalization and quantification of somatic copy number alterations in heterogeneous tumor
title BACOM2.0 facilitates absolute normalization and quantification of somatic copy number alterations in heterogeneous tumor
title_full BACOM2.0 facilitates absolute normalization and quantification of somatic copy number alterations in heterogeneous tumor
title_fullStr BACOM2.0 facilitates absolute normalization and quantification of somatic copy number alterations in heterogeneous tumor
title_full_unstemmed BACOM2.0 facilitates absolute normalization and quantification of somatic copy number alterations in heterogeneous tumor
title_short BACOM2.0 facilitates absolute normalization and quantification of somatic copy number alterations in heterogeneous tumor
title_sort bacom2.0 facilitates absolute normalization and quantification of somatic copy number alterations in heterogeneous tumor
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4563570/
https://www.ncbi.nlm.nih.gov/pubmed/26350498
http://dx.doi.org/10.1038/srep13955
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