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MAGI: Methylation analysis using genome information
By incorporating annotation information into the analysis of next-generation sequencing DNA methylation data, we provide an improvement in performance over current testing procedures. Methylation analysis using genome information (MAGI) is applicable for both unreplicated and replicated data, and pr...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Landes Bioscience
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4063829/ https://www.ncbi.nlm.nih.gov/pubmed/24589664 http://dx.doi.org/10.4161/epi.28322 |
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author | Baumann, Douglas D Doerge, RW |
author_facet | Baumann, Douglas D Doerge, RW |
author_sort | Baumann, Douglas D |
collection | PubMed |
description | By incorporating annotation information into the analysis of next-generation sequencing DNA methylation data, we provide an improvement in performance over current testing procedures. Methylation analysis using genome information (MAGI) is applicable for both unreplicated and replicated data, and provides an effective analysis for studies with low sequencing depth. When compared with current tests, the annotation-informed tests provide an increase in statistical power and offer a significance-based interpretation of differential methylation. |
format | Online Article Text |
id | pubmed-4063829 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Landes Bioscience |
record_format | MEDLINE/PubMed |
spelling | pubmed-40638292015-05-01 MAGI: Methylation analysis using genome information Baumann, Douglas D Doerge, RW Epigenetics Brief Report By incorporating annotation information into the analysis of next-generation sequencing DNA methylation data, we provide an improvement in performance over current testing procedures. Methylation analysis using genome information (MAGI) is applicable for both unreplicated and replicated data, and provides an effective analysis for studies with low sequencing depth. When compared with current tests, the annotation-informed tests provide an increase in statistical power and offer a significance-based interpretation of differential methylation. Landes Bioscience 2014-05-01 2014-03-31 /pmc/articles/PMC4063829/ /pubmed/24589664 http://dx.doi.org/10.4161/epi.28322 Text en Copyright © 2014 Landes Bioscience http://creativecommons.org/licenses/by-nc/3.0/ This is an open-access article licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License. The article may be redistributed, reproduced, and reused for non-commercial purposes, provided the original source is properly cited. |
spellingShingle | Brief Report Baumann, Douglas D Doerge, RW MAGI: Methylation analysis using genome information |
title | MAGI: Methylation analysis using genome information |
title_full | MAGI: Methylation analysis using genome information |
title_fullStr | MAGI: Methylation analysis using genome information |
title_full_unstemmed | MAGI: Methylation analysis using genome information |
title_short | MAGI: Methylation analysis using genome information |
title_sort | magi: methylation analysis using genome information |
topic | Brief Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4063829/ https://www.ncbi.nlm.nih.gov/pubmed/24589664 http://dx.doi.org/10.4161/epi.28322 |
work_keys_str_mv | AT baumanndouglasd magimethylationanalysisusinggenomeinformation AT doergerw magimethylationanalysisusinggenomeinformation |