23.integrative-DMR-DEG/SKILL.md
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.
npx skillsauth add bisnake2001/chromskills integrative-DMR-DEGInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill integrates differential methylation and differential expression datasets to reveal coordinated epigenetic regulation patterns.
dmr_results.txt # DMR results output by the metilene
dge_result.csv # DEG results output by DESeq2
corr_DMR_DEG/
stats/
integrated_results.tsv
pattern_counts.tsv
summary_stats.tsv
correlation_plot.pdf
temp/
homer_dmr.bed
... # Other temp files
awk -F'\t' 'BEGIN {OFS="\t"} {print $1, $2, $3, "peak_"NR, "*", "+"}' dmr_results.txt > homer_dmr.bed
Call:
with:
peaks_path: 6-column standard format BED file from Step 1.genome: Provide by user.output_path: Output path of the annotated fileCall:
(1) with:
input_path: dmr_results.txtoutput_pathdata_type: methylsource: metilene(2) with:
input_path: dge_result.csvoutput_pathdata_type: exprsource: deseq2Call:
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).
development
Align ChIP-seq or ATAC-seq FASTQ files to a reference genome using Bowtie2, with strict input validation, library layout detection, output organization and logging. Use it when raw sequencing reads must be converted into sorted/indexed BAM files before downstream QC, peak calling, or footprinting.
development
Align bisulfite sequencing DNA methylation reads using Bismark only, with explicit validation of reference preparation, library layout detection, output organization, logging, and alignment QC. Use it for WGBS, RRBS, or other bisulfite-converted DNA methylation sequencing data when raw FASTQ files must be aligned before methylation extraction and downstream analysis.
data-ai
Perform peak calling for ChIP-seq or ATAC-seq data using MACS3, with intelligent parameter detection from user feedback. Use it when you want to call peaks for ChIP-seq data or ATAC-seq data.
devops
The TF-differential-binding pipeline performs differential transcription factor (TF) binding analysis from ChIP-seq datasets (TF peaks) using the DiffBind package in R. It identifies genomic regions where TF binding intensity significantly differs between experimental conditions (e.g., treatment vs. control, mutant vs. wild-type). Use the TF-differential-binding pipeline when you need to analyze the different function of the same TF across two or more biological conditions, cell types, or treatments using ChIP-seq data or TF binding peaks. This pipeline is ideal for studying regulatory mechanisms that underlie transcriptional differences or epigenetic responses to perturbations.