4.ATACseq-QC/SKILL.md
--- name: ATACseq-QC description:Performs ATAC-specific biological validation. It calculates metrics unique to chromatin accessibility assays, such as TSS enrichment scores and fragment size distributions (nucleosome banding patterns). Use this skill when you have filtered BAM file and have called peak for the file. Do NOT use this skill for ChIP-seq data or general alignment statistics. --- # ATAC-seq Quality Control ## Overview This skill performs complete ATAC-seq data quality control from
npx skillsauth add bisnake2001/chromskills 4.ATACseq-QCInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill performs complete ATAC-seq data quality control from BAM and peak files.
Main steps include:
${proj_dir} in Step 0.${sample}.bam # filtered bam files
${sample}.narrowPeak
all_atac_qc/
${sample}_qc_results/
ataqv_metrics.json
ataqv_report.html/
temp/
Call:
mcp__project-init-tools__project_initwith:
sample: alltask: atac_qcgenome: provided by userThe tool will:
all_atac_qc directory.all_atac_qc directory, which will be used as ${proj_dir}.samtools view <sample>.bam | head -n 10 | cut -f 3
Call:
with:
genome: Genome name (e.g., hg38), provided by usertemp_dir: ${proj_dir}/tempbam_uses_chr: True if BAM uses 'chr' prefix (chr1), False if not (1).Call:
mcp__qc-tools__run_ataqv_qc
bam_file: Path to filtered BAM file
peak_file: Path to peak file (narrowPeak) corresponding to the BAM file
tss_file: ${proj_dir}/temp/${genome}.tss
species: Species used, choose from (fly, human, mouse, rat, worm, yeast)
bam_uses_chr: True if BAM uses 'chr' prefix (chr1), False if not (1).
output_dir: ${proj_dir}/${sample}_qc_results
autosomal_ref_path: Provided if bam_uses_chr is False, ${proj_dir}/temp/${genome}.autosomal.ref
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.