Identifying tumorigenic non-coding mutations through altered cis-regulation

Authors

Zhongshan Cheng, Queen’s University
Michael Vermeulen, Queen’s University
Micheal Rollins-Green, Queen’s University
Tomas Babak, Queen’s University
Brian DeVeale, UCSF School of Medicine

Document Type

Article

Publication Title

STAR Protocols

Publication Date

12-17-2021

Volume

2

Issue

4

Keywords

Bioinformatics, Cancer, Genomics, RNAseq, Sequence analysis

DOI

10.1016/j.xpro.2021.100934

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).

E-ISSN

26661667

PubMed ID

34816127

Recommended Citation

Cheng, Zhongshan; Vermeulen, Michael; Rollins-Green, Micheal; Babak, Tomas; and DeVeale, Brian. (2021). Identifying tumorigenic non-coding mutations through altered cis-regulation. STAR Protocols, 2 (4).
https://scholar.uwindsor.ca/biomedpub/16