alignment-level-QC

Calculates technical mapping statistics for any aligned BAM file (ChIP or ATAC). It assesses the performance of the aligner itself by generating metrics on read depth, mapping quality, error rates, and read group data using samtools and Picard.Use this skill to check "how well the reads mapped" o...

diegosouzapw/awesome-omni-skill·0installs62stars

SKILL.md

Full skill instructions

Alignment Quality Control for ChIP-seq/ATAC-seq

Overview

Perform comprehensive preliminary alignment-level quality control for ChIP-seq and ATAC-seq BAM files using samtools, Picard, and MultiQC.

Main steps include:

Initialize the project directory.
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.
Sort and add read groups if missing in the BAM file.
Run preliminary QC metrics
Generate MultiQC report

When to use this skill

Use skill when you want to perform alignment-level quality control for ChIP-seq or ATAC-seq BAM files.

Inputs & Outputs

Inputs

<sample>.bam

Outputs

alignment_qc/
  ${sample}.bam                        # Original input
  ${sample}.sorted.bam                 # (Optional) Created if sorting was needed
  ${sample}.RG.bam                     # (Optional) Created if RG was needed
  ${sample}.RG.bam.bai                 # Index file
  qc_results/
    ${sample}.flagstat.txt
    ${sample}.stats.txt
    ${sample}.insertsize_metrics.txt
    ${sample}.dup_metrics.txt
    alignment_qc_report.html      # Visual MultiQC report
    qc_summary.txt                # Pass/Warn/Fail table
  temp/
    ${sample}.markdup.bam            # Intermediate file (safe to delete later)
    ...

Decision Tree

Step 0: Initialize Project

Call:

mcp__project-init-tools__project_init

with:

sample: all
task: alignment_qc

The tool will:

Create ${sample}_alignment_qc directory.
Return the full path of the ${sample}_alignment_qc directory, which will be used as ${proj_dir}.

Step 1: Check and Fix BAMs

Ensure all BAM files are coordinate-sorted, have Read Groups, and are indexed. This tool will skip files that are already correct and only create temporary files when fixes are needed.

Call:

mcp__qc-tools__check_and_fix_bams

with:

bam_files: List of BAM files to process.
temp_dir: ${proj_dir}/temp

Step 2: Run Alignment QC Metrics

Call:

mcp__qc-tools__run_bam_qc

with:

bam_files: List of BAM files to process.
qc_dir: ${proj_dir}/qc_results
temp_dir: ${proj_dir}/temp

Step 3: Generate Summary Report

Call:

mcp__qc-tools__generate_qc_report

with:

qc_dir: ${proj_dir}/qc_results

Quality Assessment

Key QC Metrics

Total reads – overall sequencing depth
Mapped reads (%) – alignment efficiency
Properly paired (%) – valid pair fraction (paired-end)
Duplicate rate (%) – PCR duplication estimate
Mitochondrial reads (%) – mitochondrial contamination
Insert size distribution – fragment length profile

All metrics are derived from samtools/Picard and summarized by MultiQC.

Quality Thresholds

Category	Criteria	Interpretation
Pass	All metrics within recommended thresholds	Suitable for downstream analysis
Warn	One or more borderline metrics	Likely acceptable; review recommended
Fail	Critical metrics outside acceptable ranges	Re-sequencing or reprocessing suggested

Report Generation

After MultiQC completes, generate a sample-wise summary (PASS/WARN/FAIL) per thresholds in references/qc_metrics.md and save it as:

qc_results/qc_summary.txt

Resources

Use references/qc_metrics.md for:

Metric definitions and recommended thresholds
Troubleshooting guidance
Readiness criteria for peak calling
Pointers to ENCODE/nf-core QC standards

Install skill

Copy and run in your terminal

npx -y skills add https://github.com/diegosouzapw/awesome-omni-skill --skill alignment-level-qc-majiayu000

View on GitHub

skills/development/alignment-level-qc-majiayu000/SKILL.md

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