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Application of novel and existing methods to identify genes with evidence of epigenetic association: results from GAW20
BACKGROUND: The rise in popularity and accessibility of DNA methylation data to evaluate epigenetic associations with disease has led to numerous methodological questions. As part of GAW20, our working group of 8 research groups focused on gene searching methods. RESULTS: Although the methods were v...
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/PMC6157126/ https://www.ncbi.nlm.nih.gov/pubmed/30255777 http://dx.doi.org/10.1186/s12863-018-0647-2 |
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author | Fuady, Angga M. Lent, Samantha Sarnowski, Chloé Tintle, Nathan L. |
author_facet | Fuady, Angga M. Lent, Samantha Sarnowski, Chloé Tintle, Nathan L. |
author_sort | Fuady, Angga M. |
collection | PubMed |
description | BACKGROUND: The rise in popularity and accessibility of DNA methylation data to evaluate epigenetic associations with disease has led to numerous methodological questions. As part of GAW20, our working group of 8 research groups focused on gene searching methods. RESULTS: Although the methods were varied, we identified 3 main themes within our group. First, many groups tackled the question of how best to use pedigree information in downstream analyses, finding that (a) the use of kinship matrices is common practice, (b) ascertainment corrections may be necessary, and (c) pedigree information may be useful for identifying parent-of-origin effects. Second, many groups also considered multimarker versus single-marker tests. Multimarker tests had modestly improved power versus single-marker methods on simulated data, and on real data identified additional associations that were not identified with single-marker methods, including identification of a gene with a strong biological interpretation. Finally, some of the groups explored methods to combine single-nucleotide polymorphism (SNP) and DNA methylation into a single association analysis. CONCLUSIONS: A causal inference method showed promise at discovering new mechanisms of SNP activity; gene-based methods of summarizing SNP and DNA methylation data also showed promise. Even though numerous questions still remain in the analysis of DNA methylation data, our discussions at GAW20 suggest some emerging best practices. |
format | Online Article Text |
id | pubmed-6157126 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-61571262018-10-01 Application of novel and existing methods to identify genes with evidence of epigenetic association: results from GAW20 Fuady, Angga M. Lent, Samantha Sarnowski, Chloé Tintle, Nathan L. BMC Genet Methodology BACKGROUND: The rise in popularity and accessibility of DNA methylation data to evaluate epigenetic associations with disease has led to numerous methodological questions. As part of GAW20, our working group of 8 research groups focused on gene searching methods. RESULTS: Although the methods were varied, we identified 3 main themes within our group. First, many groups tackled the question of how best to use pedigree information in downstream analyses, finding that (a) the use of kinship matrices is common practice, (b) ascertainment corrections may be necessary, and (c) pedigree information may be useful for identifying parent-of-origin effects. Second, many groups also considered multimarker versus single-marker tests. Multimarker tests had modestly improved power versus single-marker methods on simulated data, and on real data identified additional associations that were not identified with single-marker methods, including identification of a gene with a strong biological interpretation. Finally, some of the groups explored methods to combine single-nucleotide polymorphism (SNP) and DNA methylation into a single association analysis. CONCLUSIONS: A causal inference method showed promise at discovering new mechanisms of SNP activity; gene-based methods of summarizing SNP and DNA methylation data also showed promise. Even though numerous questions still remain in the analysis of DNA methylation data, our discussions at GAW20 suggest some emerging best practices. BioMed Central 2018-09-17 /pmc/articles/PMC6157126/ /pubmed/30255777 http://dx.doi.org/10.1186/s12863-018-0647-2 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 | Methodology Fuady, Angga M. Lent, Samantha Sarnowski, Chloé Tintle, Nathan L. Application of novel and existing methods to identify genes with evidence of epigenetic association: results from GAW20 |
title | Application of novel and existing methods to identify genes with evidence of epigenetic association: results from GAW20 |
title_full | Application of novel and existing methods to identify genes with evidence of epigenetic association: results from GAW20 |
title_fullStr | Application of novel and existing methods to identify genes with evidence of epigenetic association: results from GAW20 |
title_full_unstemmed | Application of novel and existing methods to identify genes with evidence of epigenetic association: results from GAW20 |
title_short | Application of novel and existing methods to identify genes with evidence of epigenetic association: results from GAW20 |
title_sort | application of novel and existing methods to identify genes with evidence of epigenetic association: results from gaw20 |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6157126/ https://www.ncbi.nlm.nih.gov/pubmed/30255777 http://dx.doi.org/10.1186/s12863-018-0647-2 |
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