Can I use this for quality control of sequencing replicates?

Yes, it includes specialized tools for multi-sample comparison, allowing you to generate PCA plots and Pearson/Spearman correlation heatmaps to verify replicate consistency.

How does the skill handle genomic normalization?

The skill provides precise guidance on applying RPGC (1x coverage), CPM, RPKM, and BPM normalization methods based on your specific experiment type and organism.

What sequencing types does this deepTools skill support?

It provides optimized workflows and commands for several high-throughput sequencing methods, including ChIP-seq, RNA-seq, ATAC-seq, and MNase-seq.

Does it include genome size data for different species?

Yes, it contains a reference table of effective genome sizes for major organisms including Human (GRCh38), Mouse (GRCm38), Zebrafish, Drosophila, and C. elegans.

deepTools NGS Analysis

Name: deepTools NGS Analysis
Author: Microck

byMicrock

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データサイエンスとML

Processes and analyzes high-throughput sequencing data to generate publication-quality genomic visualizations and quality control metrics.

概要

deepTools is a specialized Claude Code skill designed for bioinformaticians and researchers working with Next-Generation Sequencing (NGS) data. It provides expert guidance for transforming raw BAM alignments into normalized coverage tracks, performing rigorous quality control, and creating sophisticated genomic visualizations. Whether you are analyzing ChIP-seq, RNA-seq, or ATAC-seq data, this skill automates complex command-line workflows, ensures the use of correct normalization methods like RPGC or CPM, and provides standardized parameters for major model organisms to ensure reproducible and accurate genomic analysis.

主な機能

Seamless BAM to bigWig conversion with advanced normalization options
High-resolution visualization tools for heatmaps and profile plots around TSS/peaks
Specialized processing for ATAC-seq Tn5 shift correction and RNA-seq strand specificity
Automated QC workflows including PCA, correlation, and fingerprint plots
81 GitHub stars
Pre-configured effective genome size references for Human, Mouse, and more

ユースケース

Generating normalized signal tracks for publication-quality genomic visualization
Profiling protein-DNA binding enrichment patterns around transcription start sites
Assessing sequencing depth and replicate reproducibility across large NGS datasets

概要

主な機能

Seamless BAM to bigWig conversion with advanced normalization options
High-resolution visualization tools for heatmaps and profile plots around TSS/peaks
Specialized processing for ATAC-seq Tn5 shift correction and RNA-seq strand specificity
Automated QC workflows including PCA, correlation, and fingerprint plots
81 GitHub stars
Pre-configured effective genome size references for Human, Mouse, and more

ユースケース

Generating normalized signal tracks for publication-quality genomic visualization
Profiling protein-DNA binding enrichment patterns around transcription start sites
Assessing sequencing depth and replicate reproducibility across large NGS datasets