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MOABS: model based analysis of bisulfite sequencing data

Bisulfite sequencing (BS-seq) is the gold standard for studying genome-wide DNA methylation. We developed MOABS to increase the speed, accuracy, statistical power and biological relevance of BS-seq data analysis. MOABS detects differential methylation with 10-fold coverage at single-CpG resolution b...

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Detalles Bibliográficos
Autores principales: Sun, Deqiang, Xi, Yuanxin, Rodriguez, Benjamin, Park, Hyun Jung, Tong, Pan, Meong, Mira, Goodell, Margaret A, Li, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4054608/
https://www.ncbi.nlm.nih.gov/pubmed/24565500
http://dx.doi.org/10.1186/gb-2014-15-2-r38
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author Sun, Deqiang
Xi, Yuanxin
Rodriguez, Benjamin
Park, Hyun Jung
Tong, Pan
Meong, Mira
Goodell, Margaret A
Li, Wei
author_facet Sun, Deqiang
Xi, Yuanxin
Rodriguez, Benjamin
Park, Hyun Jung
Tong, Pan
Meong, Mira
Goodell, Margaret A
Li, Wei
author_sort Sun, Deqiang
collection PubMed
description Bisulfite sequencing (BS-seq) is the gold standard for studying genome-wide DNA methylation. We developed MOABS to increase the speed, accuracy, statistical power and biological relevance of BS-seq data analysis. MOABS detects differential methylation with 10-fold coverage at single-CpG resolution based on a Beta-Binomial hierarchical model and is capable of processing two billion reads in 24 CPU hours. Here, using simulated and real BS-seq data, we demonstrate that MOABS outperforms other leading algorithms, such as Fisher’s exact test and BSmooth. Furthermore, MOABS analysis can be easily extended to differential 5hmC analysis using RRBS and oxBS-seq. MOABS is available at http://code.google.com/p/moabs/.
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spelling pubmed-40546082014-06-12 MOABS: model based analysis of bisulfite sequencing data Sun, Deqiang Xi, Yuanxin Rodriguez, Benjamin Park, Hyun Jung Tong, Pan Meong, Mira Goodell, Margaret A Li, Wei Genome Biol Method Bisulfite sequencing (BS-seq) is the gold standard for studying genome-wide DNA methylation. We developed MOABS to increase the speed, accuracy, statistical power and biological relevance of BS-seq data analysis. MOABS detects differential methylation with 10-fold coverage at single-CpG resolution based on a Beta-Binomial hierarchical model and is capable of processing two billion reads in 24 CPU hours. Here, using simulated and real BS-seq data, we demonstrate that MOABS outperforms other leading algorithms, such as Fisher’s exact test and BSmooth. Furthermore, MOABS analysis can be easily extended to differential 5hmC analysis using RRBS and oxBS-seq. MOABS is available at http://code.google.com/p/moabs/. BioMed Central 2014 2014-02-24 /pmc/articles/PMC4054608/ /pubmed/24565500 http://dx.doi.org/10.1186/gb-2014-15-2-r38 Text en Copyright © 2014 Sun et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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 Method
Sun, Deqiang
Xi, Yuanxin
Rodriguez, Benjamin
Park, Hyun Jung
Tong, Pan
Meong, Mira
Goodell, Margaret A
Li, Wei
MOABS: model based analysis of bisulfite sequencing data
title MOABS: model based analysis of bisulfite sequencing data
title_full MOABS: model based analysis of bisulfite sequencing data
title_fullStr MOABS: model based analysis of bisulfite sequencing data
title_full_unstemmed MOABS: model based analysis of bisulfite sequencing data
title_short MOABS: model based analysis of bisulfite sequencing data
title_sort moabs: model based analysis of bisulfite sequencing data
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4054608/
https://www.ncbi.nlm.nih.gov/pubmed/24565500
http://dx.doi.org/10.1186/gb-2014-15-2-r38
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