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Figure 1 | BMC Genomics

Figure 1

From: Detection of differentially methylated regions from bisulfite-seq data by hidden Markov models incorporating genome-wide methylation level distributions

Figure 1

ComMet: an HMM-based framework for DMR detection from bisulfite-seq data. (a) HMM architecture. The HMM has pairs of states for CpG positions and their interval positions (named gap), each of which has three types of differential methylation: hypermethylation (Up), hypomethylation (Down), and no change (NoCh). Transition probabilities among Up, Down, and NoCh states represent distinct distance distributions among DMCs. Throughout this study, we use the dual architecture consisting of the basic and second units since it can achieve better accuracy than the basic unit only [6]. (b) Example of input bisulfite-seq data and corresponding state transitions. Colors in the state transition track correspond to those in (a).

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