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DeCAF: a novel method to identify cell-type specific regulatory variants and their role in cancer risk
Here, we propose DeCAF (DEconvoluted cell type Allele specific Function), a new method to identify cell-fraction (cf) QTLs in tumors by leveraging both allelic and total expression information. Applying DeCAF to RNA-seq data from TCGA, we identify 3664 genes with cfQTLs (at 10% FDR) in 14 cell types...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9264694/ https://www.ncbi.nlm.nih.gov/pubmed/35804456 http://dx.doi.org/10.1186/s13059-022-02708-9 |
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author | Kalita, Cynthia A. Gusev, Alexander |
author_facet | Kalita, Cynthia A. Gusev, Alexander |
author_sort | Kalita, Cynthia A. |
collection | PubMed |
description | Here, we propose DeCAF (DEconvoluted cell type Allele specific Function), a new method to identify cell-fraction (cf) QTLs in tumors by leveraging both allelic and total expression information. Applying DeCAF to RNA-seq data from TCGA, we identify 3664 genes with cfQTLs (at 10% FDR) in 14 cell types, a 5.63× increase in discovery over conventional interaction-eQTL mapping. cfQTLs replicated in external cell-type-specific eQTL data are more enriched for cancer risk than conventional eQTLs. Our new method, DeCAF, empowers the discovery of biologically meaningful cfQTLs from bulk RNA-seq data in moderately sized studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s13059-022-02708-9). |
format | Online Article Text |
id | pubmed-9264694 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-92646942022-07-09 DeCAF: a novel method to identify cell-type specific regulatory variants and their role in cancer risk Kalita, Cynthia A. Gusev, Alexander Genome Biol Method Here, we propose DeCAF (DEconvoluted cell type Allele specific Function), a new method to identify cell-fraction (cf) QTLs in tumors by leveraging both allelic and total expression information. Applying DeCAF to RNA-seq data from TCGA, we identify 3664 genes with cfQTLs (at 10% FDR) in 14 cell types, a 5.63× increase in discovery over conventional interaction-eQTL mapping. cfQTLs replicated in external cell-type-specific eQTL data are more enriched for cancer risk than conventional eQTLs. Our new method, DeCAF, empowers the discovery of biologically meaningful cfQTLs from bulk RNA-seq data in moderately sized studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s13059-022-02708-9). BioMed Central 2022-07-08 /pmc/articles/PMC9264694/ /pubmed/35804456 http://dx.doi.org/10.1186/s13059-022-02708-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Method Kalita, Cynthia A. Gusev, Alexander DeCAF: a novel method to identify cell-type specific regulatory variants and their role in cancer risk |
title | DeCAF: a novel method to identify cell-type specific regulatory variants and their role in cancer risk |
title_full | DeCAF: a novel method to identify cell-type specific regulatory variants and their role in cancer risk |
title_fullStr | DeCAF: a novel method to identify cell-type specific regulatory variants and their role in cancer risk |
title_full_unstemmed | DeCAF: a novel method to identify cell-type specific regulatory variants and their role in cancer risk |
title_short | DeCAF: a novel method to identify cell-type specific regulatory variants and their role in cancer risk |
title_sort | decaf: a novel method to identify cell-type specific regulatory variants and their role in cancer risk |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9264694/ https://www.ncbi.nlm.nih.gov/pubmed/35804456 http://dx.doi.org/10.1186/s13059-022-02708-9 |
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