Identifying tumorigenic non-coding mutations through altered cis-regulation
Summary: 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 w...
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Elsevier
2021
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oai:doaj.org-article:6395de5f28e04b289848e10d875069122021-11-10T04:41:26ZIdentifying tumorigenic non-coding mutations through altered cis-regulation2666-166710.1016/j.xpro.2021.100934https://doaj.org/article/6395de5f28e04b289848e10d875069122021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2666166721006407https://doaj.org/toc/2666-1667Summary: 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).Zhongshan ChengMichael VermeulenMicheal Rollins-GreenTomas BabakBrian DeVealeElsevierarticleBioinformaticsSequence analysisCancerGenomicsRNAseqScience (General)Q1-390ENSTAR Protocols, Vol 2, Iss 4, Pp 100934- (2021) |
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DOAJ |
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DOAJ |
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Bioinformatics Sequence analysis Cancer Genomics RNAseq Science (General) Q1-390 |
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Bioinformatics Sequence analysis Cancer Genomics RNAseq Science (General) Q1-390 Zhongshan Cheng Michael Vermeulen Micheal Rollins-Green Tomas Babak Brian DeVeale Identifying tumorigenic non-coding mutations through altered cis-regulation |
description |
Summary: 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). |
format |
article |
author |
Zhongshan Cheng Michael Vermeulen Micheal Rollins-Green Tomas Babak Brian DeVeale |
author_facet |
Zhongshan Cheng Michael Vermeulen Micheal Rollins-Green Tomas Babak Brian DeVeale |
author_sort |
Zhongshan Cheng |
title |
Identifying tumorigenic non-coding mutations through altered cis-regulation |
title_short |
Identifying tumorigenic non-coding mutations through altered cis-regulation |
title_full |
Identifying tumorigenic non-coding mutations through altered cis-regulation |
title_fullStr |
Identifying tumorigenic non-coding mutations through altered cis-regulation |
title_full_unstemmed |
Identifying tumorigenic non-coding mutations through altered cis-regulation |
title_sort |
identifying tumorigenic non-coding mutations through altered cis-regulation |
publisher |
Elsevier |
publishDate |
2021 |
url |
https://doaj.org/article/6395de5f28e04b289848e10d87506912 |
work_keys_str_mv |
AT zhongshancheng identifyingtumorigenicnoncodingmutationsthroughalteredcisregulation AT michaelvermeulen identifyingtumorigenicnoncodingmutationsthroughalteredcisregulation AT michealrollinsgreen identifyingtumorigenicnoncodingmutationsthroughalteredcisregulation AT tomasbabak identifyingtumorigenicnoncodingmutationsthroughalteredcisregulation AT briandeveale identifyingtumorigenicnoncodingmutationsthroughalteredcisregulation |
_version_ |
1718440563068370944 |