RNA-SSNV: A Reliable Somatic Single Nucleotide Variant Identification Framework for Bulk RNA-Seq Data

Abstract

The usage of expressed somatic mutations may have a unique advantage in identifying active cancer driver mutations. However, accurately calling mutations from RNA-seq data is difficult due to confounding factors such as RNA-editing, reverse transcription, and gap alignment. In the present study, we proposed a framework (named RNA-SSNV, https://github.com/pmglab/RNA-SSNV) to call somatic single nucleotide variants (SSNV) from tumor bulk RNA-seq data. Based on a comprehensive multi-filtering strategy and a machine-learning classification model trained with comprehensively curated features, RNA-SSNV achieved the best precision–recall rate (0.880–0.884) in a testing dataset and robustly retained 0.94 AUC for the precision–recall curve in three validation adult-based TCGA (The Cancer Genome Atlas) datasets. We further showed that the somatic mutations called by RNA-SSNV tended to have a higher functional impact and therapeutic power in known driver genes. Furthermore, VAF (variant allele fraction) analysis revealed that subclonal harboring expressed mutations had evolutional selection advantage and RNA had higher detection power to rescue DNA-omitted mutations. In sum, RNA-SSNV will be a useful approach to accurately call expressed somatic mutations for a more insightful analysis of cancer drive genes and carcinogenic mechanisms.

Genotype prediction of 336,463 samples from public expression data

“…De-novo variant calling from RNA-seq data has gained popularity in non-human studies due to lower costs and lack of an accurate reference genome (Adetunji et al, 2019; Jehl et al, 2021; Bakhtiarizadeh, Alamouti, 2020). Genotype calling based on the reference genome has been widely used for human samples using the Genome Analysis Toolkit (GATK) (DePristo et al, 2011; Long et al, 2022; Tang et al, 2014; Deelen et al, 2015; Vigorito et al, 2023). However, the GATK tool introduces two problems for genotyping in Recount3; 1) To overcome the storage burden, Recount3 does not provide access to raw FASTQ files which is needed as an input for GATK pipeline.…”