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, Amilia, Li, Shantao, Li, Lize, Kelso, Sean, MC3 Working Group, , PCAWG novel somatic mutation calling methods working group, , Saksena, Gordon, Ellrott, Kyle, Wendl, Michael C., Wheeler, David A., Getz, Gad, Simpson, Jared T., Gerstein, Mark B., Ding, Li, and PCAWG Consortium, (2020) Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples. Nature Communications, 11. 4748.
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Abstract
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.
| Item ID: | 68183 |
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| Item Type: | Article (Research - C1) |
| ISSN: | 2041-1723 |
| Copyright Information: | © The Author(s) 2020, corrected publication 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/. |
| Additional Information: | Matthew Field is a member of the PCAWG Consortium. |
| Research Data: | https://dcc.icgc.org/releases/PCAWG |
| Date Deposited: | 28 May 2021 01:08 |
| FoR Codes: | 31 BIOLOGICAL SCIENCES > 3105 Genetics > 310508 Genome structure and regulation @ 30% 32 BIOMEDICAL AND CLINICAL SCIENCES > 3211 Oncology and carcinogenesis > 321103 Cancer genetics @ 70% |
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