RT Journal Article
SR Electronic
T1 Identification of cancer drivers from tumor-only RNA-seq with RNA-VACAY
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2022.05.10.491431
DO 10.1101/2022.05.10.491431
A1 Jon Akutagawa
A1 Allysia J Mak
A1 Julie L Aspden
A1 Angela N Brooks
YR 2022
UL http://biorxiv.org/content/early/2022/05/11/2022.05.10.491431.abstract
AB Detecting somatic mutations is a cornerstone of cancer genomics and clinical genotyping; however, there has been little systematic evaluation of the utility of RNA sequencing (RNA-seq) for somatic variant detection and driver mutation analysis. Variants found in RNA-Seq are also expressed, reducing the identification of passenger mutations and would not suffer from annotation bias observed in whole-exome sequencing (WES). We developed RNA-VACAY, a containerized pipeline that automates somatic variant calling from tumor RNA-seq data, alone, and evaluated its performance on simulated data and 1,349 RNA-seq samples with matched whole-genome sequencing (WGS). RNA-VACAY was able to detect at least 1 putative driver gene in 15 out of 16 cancer types and identified known driver mutations in 5’ and 3’ UTRs. The computational cost and time to generate and analyze RNA-seq data is lower than WGS or WES, which decreases the resources necessary for somatic variant detection. This study demonstrates the utility of RNA-seq to detect cancer drivers.Competing Interest StatementA.N.B. is a consultant for Remix Therapeutics, Inc. All other authors have declared no competing interests.