bio-methylation-dmr-detection
Differentially methylated region (DMR) detection using methylKit tiles, bsseq BSmooth, and DMRcate. Use when identifying contiguous genomic regions with methylation differences between experimental conditions or cell types.
npx skills add majiayu000/claude-skill-registry --skill dmr-detection-gptomics-bioskills-2 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# DMR Detection ## methylKit Tile-Based DMRs ```r library(methylKit) # Read and process data meth_obj <- methRead(location = file_list, sample.id = sample_ids, treatment = treatment, assembly = 'hg38', pipeline = 'bismarkCoverage') meth_filt <- filterByCoverage(meth_obj, lo.count = 10, hi.perc = 99.9) # Create tiles (windows) tiles <- tileMethylCounts(meth_filt, win.size = 1000, step.size = 1000, cov.bases = 3) tiles_united <- unite(tiles, destrand = TRUE) # Differential methylation on tiles diff_tiles <- calculateDiffMeth(tiles_united, overdispersion = 'MN', mc.cores = 4) # Get significant DMRs dmrs <- getMethylDiff(diff_tiles, difference = 25, qvalue = 0.01) dmrs_hyper <- getMethylDiff(diff_tiles, difference = 25, qvalue = 0.01, type = 'hyper') dmrs_hypo <- getMethylDiff(diff_tiles, difference = 25, qvalue = 0.01, type = 'hypo') ``` ## bsseq BSmooth DMRs ```r library(bsseq) # Read Bismark cytosine reports bs <- read.bismark(files = c('sample1.CpG_report.txt.gz', 'sample2.CpG_report.txt.gz'), sampleNames = c('ctrl', 'treat'), rmZeroCov = TRUE, strandCollapse = TRUE) # Smooth methylation data bs_smooth <- BSmooth(bs, mc.cores = 4, verbose = TRUE) # Filter by coverage bs_cov <- getC
- methylKit Tile-Based DMRs
- bsseq BSmooth DMRs
- DMRcate Method
- Annotate DMRs with Genes
- Annotate with genomation
- Visualize DMR
- Merge Adjacent DMRs
- Export DMRs
- DMR Comparison Across Methods
- Key Parameters
- methylKit tileMethylCounts
- bsseq dmrFinder
- Related Skills
What does the bio-methylation-dmr-detection skill do?
Differentially methylated region (DMR) detection using methylKit tiles, bsseq BSmooth, and DMRcate. Use when identifying contiguous genomic regions with methylation differences between experimental conditions or cell types.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill dmr-detection-gptomics-bioskills-2 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.