deeptools

Solid

NGS analysis toolkit. BAM to bigWig conversion, QC (correlation, PCA, fingerprints), heatmaps/profiles (TSS, peaks), for ChIP-seq, RNA-seq, ATAC-seq visualization.

Data & Documents 27,984 stars 2901 forks Updated today MIT

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Skill Content

# 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:** - Convert BAM alignments to normalized coverage tracks (bigWig/bedGraph) - Quality control assessment (fingerprint, correlation, coverage) - Sample comparison and correlation analysis - Heatmap and profile plot generation around genomic features - Enrichment analysis and peak region visualization ## When to Use This Skill This skill should be used when: - **File conversion**: "Convert BAM to bigWig", "generate coverage tracks", "normalize ChIP-seq data" - **Quality control**: "check ChIP quality", "compare replicates", "assess sequencing depth", "QC analysis" - **Visualization**: "create heatmap around TSS", "plot ChIP signal", "visualize enrichment", "generate profile plot" - **Sample comparison**: "compare treatment vs control", "correlate samples", "PCA analysis" - **Analysis workflows**: "analyze ChIP-seq data", "RNA-seq coverage", "ATAC-seq analysis", "complete workflow" - **Working with specific file types**: BAM files, bigWig files, BED region files in genomics context ## Quick Start For users new to deepTools, start with file validation and common workflows: ### 1...

Details

Author
davila7
Repository
davila7/claude-code-templates
Created
11 months ago
Last Updated
today
Language
Python
License
MIT

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