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MOABS: model based analysis of bisulfite sequencing data

Deqiang Sun12, Yuanxin Xi12, Benjamin Rodriguez12, Hyun Jung Park12, Pan Tong12, Mira Meong3, Margaret A Goodell3 and Wei Li12*

Author Affiliations

1 Division of Biostatistics, Dan L. Duncan Cancer Center, Houston, TX 77030, USA

2 Department of Molecular and Cellular Biology, Houston, TX 77030, USA

3 Department of Pediatrics and Molecular & Human Genetics, Stem Cells and Regenerative Medicine Center, Baylor College of Medicine, Houston, TX 77030, USA

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Genome Biology 2014, 15:R38  doi:10.1186/gb-2014-15-2-r38

Published: 24 February 2014

Abstract

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/ webcite.