MOABS: model based analysis of bisulfite sequencing data

MOABS: model based analysis of bisulfite sequencing data. Sun, D., Xi, Y., Rodriguez, B., Park, H., Tong, P., Meong, M., Goodell, M. A, & Li, W. Genome Biology, 15(2):R38, 2014.

Paper doi abstract bibtex

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/.

@article{sun_moabs:_2014,
	title = {{MOABS}: model based analysis of bisulfite sequencing data},
	volume = {15},
	url = {http://genomebiology.com/2014/15/2/R38},
	doi = {10.1080/03610919308813135},
	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/.},
	language = {English},
	number = {2},
	journal = {Genome Biology},
	author = {Sun, Deqiang and Xi, Yuanxin and Rodriguez, Benjamin and Park, Hyun and Tong, Pan and Meong, Mira and Goodell, Margaret A and Li, Wei},
	year = {2014},
	pmid = {24565500},
	pages = {R38},
}

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