Quality Control Post-Alignment

Overview

After filtering our BAM files, we need to assess the quality of our ATAC-seq experiment using specialized metrics.

Learning Objectives

• Understand key ATAC-seq quality metrics
• Use ATAQV to generate comprehensive QC reports
• Interpret QC results to assess experiment quality

In order to assess the quality of the ATAC-seq experiment, there are several metrics that can be calculated from the aligned reads.

1. Key ATAC-seq Quality Metrics

Fragment size distribution: The distribution of fragment sizes can indicate the quality of the library preparation. A good ATAC-seq library should have a characteristic pattern with peaks corresponding to nucleosome-free regions (NFRs) and mono-, di-, and tri-nucleosomes.

TSS enrichment: The enrichment of reads at transcription start sites (TSS) is a key indicator of data quality. High-quality ATAC-seq data should show a strong enrichment of reads at TSSs.

2. ATAQV Tool

ATAQV is a specialized tool that calculates a variety of QC metrics for ATAC-seq data. It provides a comprehensive report that includes fragment size distribution, TSS enrichment, and other important metrics.

Task 1: Generate individual QC reports with ATAQV

• Create a new folder for QC results: results/02_QC_post_alignment
• Run ATAQV on each filtered BAM file to generate individual QC metrics
• Each sample will produce its own detailed QC report

Ataqv

You can find further information about ATAQC tool and commands in the Usage section here.
Ataqv needs a Transcription Start Site (TSS) reference file to compute TSS enrichment score. You will find this file in: /data/references/ENCODE_mm10_M21_TSS_reference.bed.
Source: TSS reference downloaded from ENCODE Project

Hint

Run ataqv for each *qc_bl_filt.sorted.bam file

Key parameters needed: - --tss-file: Path to TSS reference file - --metrics-file: Output JSON file path - --name: Sample name - mouse: Genome reference

Solution

mkdir -p results/02_QC_post_alignment
TSS_bed="/data/references/ENCODE_mm10_M21_TSS_reference.bed"

for sample_name in "${samples[@]}"; do
    echo "Processing sample: $sample_name"

    # run command
    ataqv --name $sample_name --metrics-file results/02_QC_post_alignment/$sample_name.ataqv.json --tss-file $TSS_bed mouse $path_bams/$sample_name.qc_bl_filt.sorted.bam > results/02_QC_post_alignment/$sample_name.ataqv.out
done

Parameter explanations: - --name: Sample name for output files
- --metrics-file: Output file for metrics in JSON format
- --tss-file: BED file with TSS locations
- mouse: Genome reference (mouse or human)
- $bam: Input BAM file

Task 2: Create multi-sample summary report

Compile all individual QC reports into a comprehensive summary. Use the mkarv tool from ATAQV to combine all JSON files into an interactive HTML report

Hint

Use mkarv command to process all *.json files

• Specify output directory name for the HTML report
• Include all JSON files with wildcard pattern

Solution

# Create summary report from all JSON files without changing directories
mkarv results/02_QC_post_alignment/summary_ataqv results/02_QC_post_alignment/*.ataqv.json

What this does:
- mkarv: Tool to create interactive HTML summary report.
- results/02_QC_post_alignment/summary_ataqv: Output directory for the HTML report.
- results/02_QC_post_alignment/*.ataqv.json: Include all JSON files using full path.

3. Interpret QC Results

Open the QC report located at: results/02_QC_post_alignment/summary_ataqv/index.html

Task 3: Assess the quality of ATAC-seq experiment

1. Overall Assessment: Do you think the experiment worked well?
2. Fragment Size Distribution: Do you see the expected nucleosome pattern?
3. TSS Enrichment: Are the TSS enrichment scores acceptable?
4. Concerning Metrics: Are there any metrics that would concern you?