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Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples
The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7505971/ https://www.ncbi.nlm.nih.gov/pubmed/32958763 http://dx.doi.org/10.1038/s41467-020-18151-y |
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author | Bailey, Matthew H. Meyerson, William U. Dursi, Lewis Jonathan Wang, Liang-Bo Dong, Guanlan Liang, Wen-Wei Weerasinghe, Amila Li, Shantao Kelso, Sean Saksena, Gordon Ellrott, Kyle Wendl, Michael C. Wheeler, David A. Getz, Gad Simpson, Jared T. Gerstein, Mark B. Ding, Li |
author_facet | Bailey, Matthew H. Meyerson, William U. Dursi, Lewis Jonathan Wang, Liang-Bo Dong, Guanlan Liang, Wen-Wei Weerasinghe, Amila Li, Shantao Kelso, Sean Saksena, Gordon Ellrott, Kyle Wendl, Michael C. Wheeler, David A. Getz, Gad Simpson, Jared T. Gerstein, Mark B. Ding, Li |
author_sort | Bailey, Matthew H. |
collection | PubMed |
description | The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts. |
format | Online Article Text |
id | pubmed-7505971 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-75059712020-10-05 Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples Bailey, Matthew H. Meyerson, William U. Dursi, Lewis Jonathan Wang, Liang-Bo Dong, Guanlan Liang, Wen-Wei Weerasinghe, Amila Li, Shantao Kelso, Sean Saksena, Gordon Ellrott, Kyle Wendl, Michael C. Wheeler, David A. Getz, Gad Simpson, Jared T. Gerstein, Mark B. Ding, Li Nat Commun Article The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts. Nature Publishing Group UK 2020-09-21 /pmc/articles/PMC7505971/ /pubmed/32958763 http://dx.doi.org/10.1038/s41467-020-18151-y Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Bailey, Matthew H. Meyerson, William U. Dursi, Lewis Jonathan Wang, Liang-Bo Dong, Guanlan Liang, Wen-Wei Weerasinghe, Amila Li, Shantao Kelso, Sean Saksena, Gordon Ellrott, Kyle Wendl, Michael C. Wheeler, David A. Getz, Gad Simpson, Jared T. Gerstein, Mark B. Ding, Li Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples |
title | Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples |
title_full | Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples |
title_fullStr | Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples |
title_full_unstemmed | Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples |
title_short | Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples |
title_sort | retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7505971/ https://www.ncbi.nlm.nih.gov/pubmed/32958763 http://dx.doi.org/10.1038/s41467-020-18151-y |
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