Agent skill
ChIPseq-QC
Performs ChIP-specific biological validation. It calculates metrics unique to protein-binding assays, such as Cross-correlation (NSC/RSC) and FRiP. Use this when you have filtered the BAM file and called peaks for ChIP-seq data. Do NOT use this skill for ATAC-seq data or general alignment statistics.
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/5-chipseq-qc
SKILL.md
Comprehensive ChIP-seq QC Pipeline
Overview
This skill performs a full ChIP-seq quality control analysis from aligned BAM files and peak files.
Main steps include:
- Refer to the Inputs & Outputs section to check inputs and build the output architecture. All the output file should located in
${proj_dir}in Step 0. - Perform cross-correlation analysis to calculate NSC and RSC.
- Compute FRiP (Fraction of Reads in Peaks) using peak files and aligned BAMs.
Inputs & Outputs
Inputs
${sample}.bam # filtered bam files
${sample}.narrowPeak # or broadPeak
Outputs
all_chip_qc/
${sample}_spp.txt
${sample}_crosscorr.pdf
${sample}_frip.txt
Step 0: Initialize Project
Call:
mcp__project-init-tools__project_init
with:
sample: alltask: atac_qc
The tool will:
- Create
all_chip_qcdirectory. - Return the full path of the
all_chip_qcdirectory, which will be used as${proj_dir}.
Step 1: Calculate Cross-Correlation Metrics (NSC, RSC)
Call:
- mcp__qc-tools__run_phantompeakqualtools with:
bam_file: Path to BAM fileoutput_dir: ${proj_dir}/
Output: ${sample}_spp.txt, ${sample}_crosscorr.pdf
Step 2: Calculate the fraction of reads falling within peak regions.
Call:
- mcp__qc-tools__calculate_frip with: bam_file: Path to BAM file. peak_file: Path to Peak file (BED/narrowPeak/broadPeak). output_dir: ${proj_dir}/
Output: ${sample}_frip.txt
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