Can it help me choose the right normalization method?

Yes, it provides specific guidance and automated parameters for various normalization methods like RPGC (1x coverage), CPM, RPKM, and BPM based on your organism and experiment type.

How does this skill assist with genomic visualization?

It simplifies the complex process of matrix computation and plotting, allowing you to generate publication-ready heatmaps and profile plots using tools like computeMatrix and plotHeatmap.

What types of sequencing data does this skill support?

The deepTools skill supports a wide range of high-throughput sequencing data types, specifically optimized for ChIP-seq, RNA-seq, ATAC-seq, and MNase-seq.

Does it handle file validation before running analysis?

Yes, the skill includes specialized validation routines to check for BAM indices, file existence, and BED format correctness to prevent pipeline failures.

Are there specific workflows for ATAC-seq?

Yes, it includes a dedicated ATAC-seq workflow that handles Tn5 offset correction using alignmentSieve and performs fragment size analysis.

deepTools NGS Analysis

Name: deepTools NGS Analysis
Author: K-Dense-AI

byK-Dense-AI

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2,188

Data Science & ML

Streamlines high-throughput sequencing data analysis by providing tools for BAM processing, quality control, and publication-quality genomic visualizations.

About

The deepTools skill for Claude Code is a specialized toolkit designed for bioinformaticians and researchers working with Next-Generation Sequencing (NGS) data. It provides domain-specific expertise for processing ChIP-seq, RNA-seq, and ATAC-seq datasets, enabling users to convert BAM alignments into normalized coverage tracks, perform rigorous quality control (such as PCA and fingerprint analysis), and generate sophisticated visualizations like heatmaps and signal profiles. By incorporating best practices for normalization methods and effective genome sizes, this skill ensures reproducible and scientifically sound genomic analysis workflows.

Key Features

Comprehensive QC suite including sample correlation, PCA, and ChIP-seq fingerprinting.
High-resolution visualization tools for heatmaps and profiles around genomic features.
2,188 GitHub stars
Automated workflow generators for standard ChIP-seq, RNA-seq, and ATAC-seq pipelines.
Integrated file validation for BAM indices, BED regions, and genomic formats.
Normalized coverage track generation (BAM to bigWig/bedGraph) using RPGC, CPM, or RPKM.

Use Cases

Comparing treatment and control samples using log2 ratio tracks to identify genomic enrichment patterns.
Visualizing signal intensity and distribution around Transcription Start Sites (TSS) for differential expression studies.
Assessing the quality and enrichment strength of ChIP-seq libraries before downstream peak calling.

About

Key Features

Comprehensive QC suite including sample correlation, PCA, and ChIP-seq fingerprinting.
High-resolution visualization tools for heatmaps and profiles around genomic features.
2,188 GitHub stars
Automated workflow generators for standard ChIP-seq, RNA-seq, and ATAC-seq pipelines.
Integrated file validation for BAM indices, BED regions, and genomic formats.
Normalized coverage track generation (BAM to bigWig/bedGraph) using RPGC, CPM, or RPKM.

Use Cases

Comparing treatment and control samples using log2 ratio tracks to identify genomic enrichment patterns.
Visualizing signal intensity and distribution around Transcription Start Sites (TSS) for differential expression studies.
Assessing the quality and enrichment strength of ChIP-seq libraries before downstream peak calling.