bio-methylation-methylkit
DNA methylation analysis with methylKit in R. Import Bismark coverage files, filter by coverage, normalize samples, and perform statistical comparisons. Use when analyzing single-base methylation patterns, comparing samples, or preparing data for DMR detection.
npx skills add majiayu000/claude-skill-registry --skill methylkit-analysis-gptomics-bioskills --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.
# methylKit Analysis ## Read Bismark Coverage Files ```r library(methylKit) file_list <- list('sample1.bismark.cov.gz', 'sample2.bismark.cov.gz', 'sample3.bismark.cov.gz', 'sample4.bismark.cov.gz') sample_ids <- c('ctrl_1', 'ctrl_2', 'treat_1', 'treat_2') treatment <- c(0, 0, 1, 1) # 0 = control, 1 = treatment meth_obj <- methRead( location = as.list(file_list), sample.id = as.list(sample_ids), treatment = treatment, assembly = 'hg38', context = 'CpG', pipeline = 'bismarkCoverage' ) ``` ## Read Bismark cytosine Report ```r meth_obj <- methRead( location = as.list(file_list), sample.id = as.list(sample_ids), treatment = treatment, assembly = 'hg38', context = 'CpG', pipeline = 'bismarkCytosineReport' ) ``` ## Basic Statistics ```r # Coverage statistics getMethylationStats(meth_obj[[1]], plot = TRUE, both.strands = FALSE) # Coverage per sample getCoverageStats(meth_obj[[1]], plot = TRUE, both.strands = FALSE) ``` ## Filter by Coverage ```r # Remove CpGs with very low or very high coverage meth_filtered <- filterByCoverage( meth_obj, lo.count = 10, # Minimum 10 reads lo.perc = NULL, hi.count = NULL, hi.perc = 99.9 # Remove top 0.1% (likely PCR artifacts) ) ``` ## Normalize Coverage ``
- Read Bismark Coverage Files
- Read Bismark cytosine Report
- Basic Statistics
- Filter by Coverage
- Normalize Coverage
- Merge Samples (Unite)
- Visualize Samples
- Differential Methylation (Single CpGs)
- Tile-Based Analysis (Regions)
- Export Results
- Annotate with Genomic Features
- Reorganize for Multi-Group Comparison
- Pool Replicates
- Key Functions
What does the bio-methylation-methylkit skill do?
DNA methylation analysis with methylKit in R. Import Bismark coverage files, filter by coverage, normalize samples, and perform statistical comparisons. Use when analyzing single-base methylation patterns, comparing samples, or preparing data for DMR detection.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill methylkit-analysis-gptomics-bioskills --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.