MultiDMPcaller: A One-Stop Software for Detection and Visualization of Differentially Methylated Positions and Regions
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ID: 327221
2026
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Abstract
MOTIVATION: Whole-genome bisulfite sequencing (WGBS/BS-Seq) is the gold standard for single-base resolution DNA methylome profiling. However, the diverse statistical models of existing computational methods lead to limited overlap between their results, highlighting the need for novel methods to detect Differentially Methylated Positions (DMPs) and Differentially Methylated Regions (DMRs). RESULTS: We developed MultiDMPcaller, an automated downstream methylome analysis software. It processes upstream outputs to profile DMPs, Non-DMPs, DMRs, and context-specific (CpG/CHG/CHH) methylation status, alongside visualizing their chromosomal distribution and enrichment. The software features two key innovations: i) An adaptive two-step p-value adjustment strategy based on organism-specific methylation patterns, with raw p-value ≤ 0.05 pre-filtering followed by false discovery rate (FDR) correction, to recover potential DMPs usually missed by standard FDR correction in plant CHG/CHH and animal CpG contexts; ii) A multiple pairwise comparison approach, which performs m×n pairwise comparisons for m control and n experimental replicates, followed by a voting system supporting both user-defined majority thresholds and model-based adaptive thresholds, to identify robust and reliable DMPs (with a stricter voting threshold exclusively for loci with low methylation differences) and DMRs. On real datasets from Arabidopsis, apple, and mouse, as well as simulated human datasets, MultiDMPcaller's results showed good agreement with those of other software, exhibiting high conservativeness and superior precision, which suggested a low false discovery proportion. AVAILABILITY: MultiDMPcaller is available at GitHub (https://github.com/jiantaoyuNWAFU/MultiDMPcaller) and via a web server (https://ciebioinfo.nwafu.edu.cn).
| Reference Key |
openalex_W7204950650
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|---|---|
| Authors | Qiuyu Yuan, Hongyan Zhao, Z. Q. Zhang, Chenhao Yue, Bingchao Zhang, Songyan Xue, Qing Zou, Jiantao Yu |
| Journal | BMC Bioinformatics |
| Year | 2026 |
| DOI |
10.1093/bioinformatics/btag655
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| URL | |
| Keywords | Keywords not found |
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