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Comparison of novel and existing methods for detecting differentially methylated regions
BACKGROUND: Single-probe analyses in epigenome-wide association studies (EWAS) have identified associations between DNA methylation and many phenotypes, but do not take into account information from neighboring probes. Methods to detect differentially methylated regions (DMRs) (clusters of neighbori...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6156895/ https://www.ncbi.nlm.nih.gov/pubmed/30255775 http://dx.doi.org/10.1186/s12863-018-0637-4 |
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author | Lent, Samantha Xu, Hanfei Wang, Lan Wang, Zhe Sarnowski, Chloé Hivert, Marie-France Dupuis, Josée |
author_facet | Lent, Samantha Xu, Hanfei Wang, Lan Wang, Zhe Sarnowski, Chloé Hivert, Marie-France Dupuis, Josée |
author_sort | Lent, Samantha |
collection | PubMed |
description | BACKGROUND: Single-probe analyses in epigenome-wide association studies (EWAS) have identified associations between DNA methylation and many phenotypes, but do not take into account information from neighboring probes. Methods to detect differentially methylated regions (DMRs) (clusters of neighboring probes associated with a phenotype) may provide more power to detect associations between DNA methylation and diseases or phenotypes of interest. RESULTS: We proposed a novel approach, GlobalP, and perform comparisons with 3 methods—DMRcate, Bumphunter, and comb-p—to identify DMRs associated with log triglycerides (TGs) in real GAW20 data before and after fenofibrate treatment. We applied these methods to the summary statistics from an EWAS performed on the methylation data. Comb-p, DMRcate, and GlobalP detected very similar DMRs near the gene CPT1A on chromosome 11 in both the pre- and posttreatment data. In addition, GlobalP detected 2 DMRs before fenofibrate treatment in the genes ETV6 and ABCG1. Bumphunter identified several DMRs on chromosomes 1 and 20, which did not overlap with DMRs detected by other methods. CONCLUSIONS: Our novel method detected the same DMR identified by two existing methods and detected two additional DMRs not identified by any of the existing methods we compared. |
format | Online Article Text |
id | pubmed-6156895 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-61568952018-09-27 Comparison of novel and existing methods for detecting differentially methylated regions Lent, Samantha Xu, Hanfei Wang, Lan Wang, Zhe Sarnowski, Chloé Hivert, Marie-France Dupuis, Josée BMC Genet Research BACKGROUND: Single-probe analyses in epigenome-wide association studies (EWAS) have identified associations between DNA methylation and many phenotypes, but do not take into account information from neighboring probes. Methods to detect differentially methylated regions (DMRs) (clusters of neighboring probes associated with a phenotype) may provide more power to detect associations between DNA methylation and diseases or phenotypes of interest. RESULTS: We proposed a novel approach, GlobalP, and perform comparisons with 3 methods—DMRcate, Bumphunter, and comb-p—to identify DMRs associated with log triglycerides (TGs) in real GAW20 data before and after fenofibrate treatment. We applied these methods to the summary statistics from an EWAS performed on the methylation data. Comb-p, DMRcate, and GlobalP detected very similar DMRs near the gene CPT1A on chromosome 11 in both the pre- and posttreatment data. In addition, GlobalP detected 2 DMRs before fenofibrate treatment in the genes ETV6 and ABCG1. Bumphunter identified several DMRs on chromosomes 1 and 20, which did not overlap with DMRs detected by other methods. CONCLUSIONS: Our novel method detected the same DMR identified by two existing methods and detected two additional DMRs not identified by any of the existing methods we compared. BioMed Central 2018-09-17 /pmc/articles/PMC6156895/ /pubmed/30255775 http://dx.doi.org/10.1186/s12863-018-0637-4 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Lent, Samantha Xu, Hanfei Wang, Lan Wang, Zhe Sarnowski, Chloé Hivert, Marie-France Dupuis, Josée Comparison of novel and existing methods for detecting differentially methylated regions |
title | Comparison of novel and existing methods for detecting differentially methylated regions |
title_full | Comparison of novel and existing methods for detecting differentially methylated regions |
title_fullStr | Comparison of novel and existing methods for detecting differentially methylated regions |
title_full_unstemmed | Comparison of novel and existing methods for detecting differentially methylated regions |
title_short | Comparison of novel and existing methods for detecting differentially methylated regions |
title_sort | comparison of novel and existing methods for detecting differentially methylated regions |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6156895/ https://www.ncbi.nlm.nih.gov/pubmed/30255775 http://dx.doi.org/10.1186/s12863-018-0637-4 |
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