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Identifying tumorigenic non-coding mutations through altered cis-regulation
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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8591365/ https://www.ncbi.nlm.nih.gov/pubmed/34816127 http://dx.doi.org/10.1016/j.xpro.2021.100934 |
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author | Cheng, Zhongshan Vermeulen, Michael Rollins-Green, Micheal Babak, Tomas DeVeale, Brian |
author_facet | Cheng, Zhongshan Vermeulen, Michael Rollins-Green, Micheal Babak, Tomas DeVeale, Brian |
author_sort | Cheng, Zhongshan |
collection | PubMed |
description | 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 | Online Article Text |
id | pubmed-8591365 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-85913652021-11-22 Identifying tumorigenic non-coding mutations through altered cis-regulation Cheng, Zhongshan Vermeulen, Michael Rollins-Green, Micheal Babak, Tomas DeVeale, Brian STAR Protoc Protocol 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). Elsevier 2021-11-08 /pmc/articles/PMC8591365/ /pubmed/34816127 http://dx.doi.org/10.1016/j.xpro.2021.100934 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Protocol Cheng, Zhongshan Vermeulen, Michael Rollins-Green, Micheal Babak, Tomas DeVeale, Brian Identifying tumorigenic non-coding mutations through altered cis-regulation |
title | 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_short | Identifying tumorigenic non-coding mutations through altered cis-regulation |
title_sort | identifying tumorigenic non-coding mutations through altered cis-regulation |
topic | Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8591365/ https://www.ncbi.nlm.nih.gov/pubmed/34816127 http://dx.doi.org/10.1016/j.xpro.2021.100934 |
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