22.local-methylation-profile/SKILL.md
This skill analyzes the local DNA methylation profiles around target genomic regions provide by user. Use this skill when you want to vasulize the average methylation profile around target regions (e.g. TSS, CTCF peak or other target regions).
npx skillsauth add bisnake2001/chromskills local-methylation-profileInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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methylation.bed
target_regions.bed
local_methyl_profile/
stats/
CpG_around_target.tsv
plots/
CpG_around_target.pdf
temp/
... # other temp file generated
awk -F'\t' 'BEGIN {OFS="\t"} {print $1, $2, $3, $<i_methylation>}, $<i_coverage>}' methylation.bed # n is provide by user, *100 if is fraction
awk -F'\t' 'BEGIN {OFS="\t"} {print $1, $2, $3}' target_regions.bed
Call:
mcp__methyl-tools__build_local_methylation_profilewith:
methyl_bed_path: 5-column BED-like file from preprocess_methylation.regions_bed_path: 3-column BED-like file from preprocess_regions.output_profile_tsv_path: path for aggregated profile table (TSV).flank_size: flank size in bp around region center (default 2000).bin_size: bin size in bp (default 50).min_coverage: minimum coverage threshold for CpGs (default 10).Call:
mcp__methyl-tools__plot_profilewith:
profile_tsv_path: TSV from build_methylation_profile.output_plot_path: output figure path (PNG/PDF; format inferred from extension).title: plot title (optional).| Context | Flank | Bin | Min cov | |-----------|-------|------|---------| | TF peaks | ±2 kb | 50bp | 10x | | Promoters | ±1 kb | 50bp | 10x | | Enhancers | ±5 kb | 100bp| 5x | | Motifs | ±0.5kb| 10–20| 10x |
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.