deepTools — NGS Data Analysis Toolkit

deepTools — NGS Data Analysis Toolkit

Overview

deepTools is a command-line toolkit for processing and visualizing high-throughput sequencing data. It converts BAM alignments to normalized coverage tracks (bigWig), performs quality control (correlation, PCA, fingerprint), and generates publication-quality heatmaps and profile plots around genomic features. Supports ChIP-seq, RNA-seq, ATAC-seq, and MNase-seq.

When to Use

• Converting BAM files to normalized bigWig coverage tracks
• Comparing ChIP-seq treatment vs input control (log2 ratio tracks)
• Assessing sample quality: replicate correlation, PCA, coverage depth
• Evaluating ChIP enrichment strength (fingerprint plots)
• Creating heatmaps and profile plots around TSS, peaks, or other genomic regions
• Analyzing ATAC-seq data with Tn5 offset correction
• Generating strand-specific RNA-seq coverage tracks
• Use omics-plotting SKILL for custom figures from exported score matrices; standard signal heatmaps/profiles use deeptools' own plotHeatmap/plotProfile
• For read alignment, use STAR, BWA, or bowtie2 instead
• For peak calling, use MACS2 or HOMER instead
• For BAM/VCF file manipulation, use pysam instead

Prerequisites

pip install deeptools
# Verify installation
bamCoverage --version

Input requirements: BAM files must be sorted and indexed (.bai file present). Generate index with samtools index input.bam. BED files for genomic regions (genes, peaks) in standard 3+ column format.

Pre-flight Interview

Settle these with the user before writing any analysis code.

decisions:
  - id: D1
    param: normalizationMethod
    kind: required
    source: user