deeptools

Convert BAM files to bigWig and visualize NGS data with deepTools.

13|3|Updated Jun 10, 2026
One-click install
npx skills add https://github.com/tassiovale/claude-code-kit --skill deeptools-tassiovale
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: deeptools
Source: https://github.com/tassiovale/claude-code-kit/tree/main/skills/deeptools
Command: npx skills add https://github.com/tassiovale/claude-code-kit --skill deeptools-tassiovale

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires deepTools, python, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides comprehensive analysis and visualization capabilities for Next-Generation Sequencing (NGS) data, enabling users to perform quality control, normalization, sample comparison, and generate publication-quality visualizations.

Core Features & Use Cases

  • Data Conversion: Convert BAM alignments to bigWig or bedGraph files for visualization.
  • Quality Control: Assess sequencing depth, perform PCA, and generate fingerprints for quality assessment.
  • Visualization: Create heatmaps, profiles, and enrichment plots for genomic features.
  • Sample Comparison: Compare samples and perform correlation analysis.
  • Use Case: Imagine you have ChIP-seq data for multiple samples. Use this Skill to normalize the data, perform quality control, visualize the signal, and compare samples to identify enriched regions.

Quick Start

Use the deepTools skill to generate a heatmap around the TSS for the ChIP-seq data in 'chip-seq_data.bam'.

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 bigWig for NGS data visualization?

This Skill converts BAM alignments to bigWig or bedGraph files using deepTools, enabling downstream NGS data visualization and quality control for ChIP-seq, RNA-seq, and ATAC-seq experiments.

Can I perform quality control and PCA on ChIP-seq data using deepTools?

Yes, this Skill performs ChIP-seq quality control using deepTools by assessing sequencing depth, executing PCA, and generating fingerprints to evaluate sample quality and identify enriched regions.

How do I generate heatmaps and profiles around TSS for RNA-seq experiments?

This Skill generates heatmaps and profiles around TSS for RNA-seq experiments by leveraging deepTools to create publication-quality enrichment plots for genomic features.

What is the best way to normalize and compare multiple NGS samples?

This Skill normalizes and compares multiple NGS samples by applying deepTools normalization functions and performing correlation analysis across ChIP-seq, RNA-seq, and ATAC-seq experiments.

Do I need Python 3.8 to run deepTools for ATAC-seq data analysis?

Yes, this Skill requires Python >3.8 and deepTools to execute ATAC-seq data analysis, including BAM to bigWig conversion, quality control, and visualization operations.