Journal of Computational BiologyGenomicsPeer-reviewed journal article
MethCP: Differentially Methylated Region Detection with Change Point Models
Abstract
Abstract.Whole-genome bisulfite sequencing (WGBS) provides a precise measure of methylation across the genome, yet presents a challenge in identifying regions that are differentially methylated (DMRs) between different conditions. A number of methods have been proposed which mainly focusing on the setting of two-group comparison. We develop a DMR detecting method MethCP for WGBS data, which is applicable for a wide range of experimental designs beyond the two-group comparisons, such as time-course data. MethCP identifies DMRs based on change point detection, which naturally segments the genome and provides region-level differential analysis. For simple two-group comparison, we show that our method outperforms developed methods in accurately detecting the complete DM region on a simulated dataset and an Arabidopsis dataset. Moreover, we show that MethCP is capable of detecting wide regions with small effect sizes, which can be common in some settings but existing techniques are poor in detecting such DMRs. We also demonstrate the use of MethCP for time-course data on another dataset following methylation throughout seed germination in Arabidopsis.
- organism: Arabidopsis
- assay: whole-genome sequencing
- research focus: differential expression
- approach: statistical model
- Citations
- 12
- FWCI
- 0.65
- Field percentile
- top 39%
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