Processes and visualizes high-throughput sequencing data for genomics research and quality control.
deepTools is a comprehensive Python-based toolkit integrated into Claude Code to streamline the analysis of Next-Generation Sequencing (NGS) data. It enables researchers and bioinformaticians to convert BAM alignments into normalized coverage tracks, perform rigorous quality control checks like fingerprinting and PCA, and generate publication-quality heatmaps or profiles. Whether working with ChIP-seq, RNA-seq, or ATAC-seq, this skill provides standardized workflows and automated scripts to ensure reproducible genomic data visualization and sample comparison.
Key Features
01BAM to bigWig/bedGraph conversion with normalization (RPGC, CPM, RPKM)
02Specialized workflows for ChIP-seq, RNA-seq, and ATAC-seq data
03File validation and workflow template generation
04Automated Quality Control (Fingerprint plots, PCA, and correlation matrices)
05Genomic feature visualization (TSS heatmaps and signal profiles)
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Use Cases
01Generating publication-ready heatmaps and profile plots for genomic regions
02Visualizing ChIP-seq signal enrichment around Transcription Start Sites (TSS)
03Normalizing and comparing treatment vs. control sequencing samples
