TY - JOUR
T1 - Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples
AU - Bailey, Matthew H.
AU - Meyerson, William U.
AU - Dursi, Lewis Jonathan
AU - Wang, Liang Bo
AU - Dong, Guanlan
AU - Liang, Wen Wei
AU - Weerasinghe, Amila
AU - Li, Shantao
AU - Kelso, Sean
AU - Akbani, Rehan
AU - Anur, Pavana
AU - Bailey, Matthew H.
AU - Buchanan, Alex
AU - Chiotti, Kami
AU - Covington, Kyle
AU - Creason, Allison
AU - Ding, Li
AU - Weischenfeldt, Joachim
AU - Brunak, Søren
AU - Ding, Li
AU - Favero, Francesco
AU - MC3 Working Group
AU - PCAWG novel somatic mutation calling methods working group
AU - PCAWG Consortium
N1 - Publisher Copyright:
© 2020, The Author(s).
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
U2 - 10.1038/s41467-020-18151-y
DO - 10.1038/s41467-020-18151-y
M3 - Journal article
C2 - 32958763
AN - SCOPUS:85079069163
VL - 11
JO - Nature Communications
JF - Nature Communications
SN - 2041-1723
IS - 1
M1 - 4748
ER -