RNAIndel: discovering somatic coding indels from tumor RNA-Seq data.

ABSTRACT:

Motivation

Reliable identification of expressed somatic insertions/deletions (indels) is an unmet need due to artifacts generated in PCR-based RNA-Seq library preparation and the lack of normal RNA-Seq data, presenting analytical challenges for discovery of somatic indels in tumor transcriptome.

Results

We present RNAIndel, a tool for predicting somatic, germline and artifact indels from tumor RNA-Seq data. RNAIndel leverages features derived from indel sequence context and biological effect in a machine-learning framework. Except for tumor samples with microsatellite instability, RNAIndel robustly predicts 88-100% of somatic indels in five diverse test datasets of pediatric and adult cancers, even recovering subclonal (VAF range 0.01-0.15) driver indels missed by targeted d

SUBMITTER: Hagiwara K 

PROVIDER: S-EPMC7523641 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature