Claude-skill-registry integrative-DMR-DEG
This skill performs correlation analysis between differential methylation and differential gene expression, identifying genes with coordinated epigenetic regulation. It provides preprocessing and integration workflows, using promoter-level methylation–expression relationships.
install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/23-integrative-dmr-deg" ~/.claude/skills/majiayu000-claude-skill-registry-integrative-dmr-deg && rm -rf "$T"
manifest:
skills/data/23-integrative-dmr-deg/SKILL.mdsource content
Integrative Methylation–Expression Correlation Analysis
Overview
This skill integrates differential methylation and differential expression datasets to reveal coordinated epigenetic regulation patterns.
- Refer to Inputs & Outputs to verify necessary files.
- Always prompt user for genome assembly used.
- Prepare the DMR regions into 6-column standard format BED file received by HOMER.
- Annotate the differential methylation regions to the gene promoter.
- Preprocess differential methylation and expression tables into a standard format.
- Integrate methylation and expression data by promoter proximity.
- Calculate correlation between methylation change and expression fold change.
- Classify patterns such as hypermethylation–downregulation or hypomethylation–upregulation.
Inputs & Outputs
Inputs
dmr_results.txt # DMR results output by the metilene dge_result.csv # DEG results output by DESeq2
Outputs
corr_DMR_DEG/ stats/ integrated_results.tsv pattern_counts.tsv summary_stats.tsv correlation_plot.pdf temp/ homer_dmr.bed ... # Other temp files
Decision Tree
Step 1: Prepare the DMR regions into 6-column standard format BED file received by HOMER
awk -F'\t' 'BEGIN {OFS="\t"} {print $1, $2, $3, "peak_"NR, "*", "+"}' dmr_results.txt > homer_dmr.bed
Step 2: Annotate the differential methylation regions to the gene promoter.
Call:
- mcp__homer-tools__homer_simple_annotate_peaks
with:
: 6-column standard format BED file from Step 1.peaks_path
: Provide by user.genome
: Output path of the annotated fileoutput_path
Step 3: Preprocess differential methylation and expression tables into a standard format
Call:
- mcp__methyl-tools__preprocess_differential_table
(1) with:
: dmr_results.txtinput_pathoutput_path
: methyldata_type
: metilenesource
(2) with:
: dge_result.csvinput_pathoutput_path
: exprdata_type
: deseq2source
Step 4: Integrate methylation and expression data by promoter proximity
Call:
- mcp__methyl-tools__integrate_methylation_expression
with:
methyl_path: Path to standardized methylation TSV with columns: chr,start,end,pvalue,meth_diff (from Step 3)
methyl_annot_path: Path to methylation annotation TSV from HOMER (from Step 2).
expr_path: Path to standardized expression TSV with columns: gene,pvalue,log2FoldChange (from Step 3).
output_prefix: Prefix for all output files (e.g. 'corr_DMR_DEG/stats/integrative').
methyl_diff: Absolute methylation difference threshold (fraction points).
expr_fc: Fold-change threshold for expression (absolute, e.g. 1.5 for 1.5x).