deeptools

Convert BAM alignments into normalized coverage tracks and generate QC metrics.

52|6|Updated Nov 24, 2025

Search Tags:#RNA-seq #ATAC-seq #NGS #deepTools #bigWig #ChIP-seq

Ready to run

npx skills add https://github.com/ovachiever/droid-tings --skill deeptools

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: deeptools
Source: https://github.com/ovachiever/droid-tings/tree/main/skills/deeptools
Command: npx skills add https://github.com/ovachiever/droid-tings --skill deeptools

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

deepTools is an NGS data analysis toolkit that streamlines QC, normalization, and visualization for ChIP-seq, RNA-seq, ATAC-seq, and more.

Core Features & Use Cases

File validation, QC metrics, and normalization workflows
Generate coverage tracks (bW/bedGraph) and compare samples
Visualization: heatmaps, profile plots, and enrichment analyses

Quick Start

Install deeptools and use the included workflows to generate QC reports and coverage plots from BAM/BigWig files.

Frequently Asked Questions about deeptools

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I convert BAM files to normalized coverage tracks for NGS analysis?▼

BAM to coverage track conversion uses bamCoverage to transform BAM alignments into bigWig or bedGraph formats with normalization methods like RPKM, CPM, BPM, RPGC, or SES, enabling standardized comparison across samples and genome sizes.

Can I compare ChIP-seq or RNA-seq samples and visualize their differences?▼

Sample comparison uses bamCompare to generate normalized difference tracks between BAM files, then plotProfile or plotHeatmap visualize enrichment patterns, fold-changes, and region-centric contrasts for publication-ready figures.

What's the best way to generate QC metrics and fingerprint plots for sequencing experiments?▼

QC assessment uses plotFingerprint to evaluate library complexity and fragment distribution, along with file validation workflows that flag alignment issues, duplication rates, and coverage anomalies before downstream analysis.

How do I create heatmaps and profile plots from BAM or bigWig files?▼

Matrix computation via computeMatrix organizes coverage data across genomic regions, then plotHeatmap and plotProfile render sorted, scaled visualizations with multiple normalization and binning options for heatmaps and aggregate profiles.

Does this work with ATAC-seq, MNase-seq, and other NGS protocols beyond ChIP-seq?▼

Yes, deepTools supports ChIP-seq, RNA-seq, ATAC-seq, MNase-seq, and related workflows by accepting BAM and bigWig inputs with configurable effective genome sizes and normalization methods across all protocol types.

What input formats and genome parameters do I need to prepare?▼

Required inputs are BAM or bigWig files and an effective genome size parameter (--effectiveGenomeSize) specific to your organism; BED files define analysis regions for matrix computation and visualization.