Identifying tumorigenic non-coding mutations through altered cis-regulation

Zhongshan Cheng; Michael Vermeulen; Micheal Rollins-Green; Tomas Babak; Brian DeVeale

doi:10.1016/j.xpro.2021.100934

Identifying tumorigenic non-coding mutations through altered cis-regulation

STAR Protoc. 2021 Nov 8;2(4):100934. doi: 10.1016/j.xpro.2021.100934. eCollection 2021 Dec 17.

Authors

Zhongshan Cheng¹, Michael Vermeulen¹, Micheal Rollins-Green¹, Tomas Babak¹, Brian DeVeale²

Affiliations

¹ Department of Biology, Queen's University, Kingston, ON K7L 3N6, Canada.
² The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94143, USA.

Abstract

Identification of non-coding mutations driving tumorigenesis requires alternative approaches to coding mutations. Enriched associations between mutated regulatory elements and altered cis-regulation in tumors are a promising approach to stratify candidate non-coding driver mutations. Here we provide a bioinformatics pipeline to mine data from the Cancer Genomic Commons (GDC) for such associations. The pipeline integrates RNA and whole-genome sequencing with genotyping data to reveal putative non-coding driver mutations by cancer type. For complete information on the generation and use of this protocol, please refer to Cheng et al. (2021).

Keywords: Bioinformatics; Cancer; Genomics; RNAseq; Sequence analysis.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Carcinogenesis / genetics*
Computational Biology / methods*
Databases, Genetic
Humans
Mutation / genetics*
Neoplasms / genetics*
Regulatory Sequences, Nucleic Acid / genetics*