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Identifying tumorigenic non-coding mutations through altered cis-regulation.


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).

SUBMITTER: Cheng Z 

PROVIDER: S-EPMC8591365 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Identifying tumorigenic non-coding mutations through altered <i>cis</i>-regulation.

Cheng Zhongshan Z   Vermeulen Michael M   Rollins-Green Micheal M   Babak Tomas T   DeVeale Brian B  

STAR protocols 20211108 4


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  ...[more]

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