Deeptools

If you're working with ChIP-seq, RNA-seq, or ATAC-seq data, this handles the standard pipeline from BAM files to publication-ready visualizations. It wraps the deepTools Python suite with workflow generators for common tasks like converting alignments to normalized bigWig tracks, running QC checks (fingerprint plots, sample correlation, PCA), and creating heatmaps around genomic features like TSSs or peaks. The skill includes validation scripts and templates for complete workflows, which is helpful since deepTools has a lot of normalization options (RPGC, CPM, RPKM) and it's easy to pick the wrong one. The quick reference and workflow documentation actually explain when to use what, which beats hunting through the official docs.

skills.sh installs: 218
GitHub stars: 33.2K
last updated: Aug 21, 2026

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Install

$ npx -y skills add davila7/claude-code-templates --skill deeptools --agent claude-code

Installs into .claude/skills of the current project.

Files

deepTools: NGS Data Analysis Toolkit

Overview

deepTools is a comprehensive suite of Python command-line tools designed for processing and analyzing high-throughput sequencing data. Use deepTools to perform quality control, normalize data, compare samples, and generate publication-quality visualizations for ChIP-seq, RNA-seq, ATAC-seq, MNase-seq, and other NGS experiments.

Core capabilities: