What file formats does this skill work with?

The skill primarily processes BAM, bigWig, BED, and bedGraph files, which are standard formats in genomic research.

Can this skill help with data normalization?

Yes, it supports multiple normalization methods like RPGC (1x genome coverage), CPM, RPKM, and BPM to ensure valid comparisons between samples.

What sequencing types are supported by deepTools?

deepTools is designed for various NGS experiments including ChIP-seq, RNA-seq, ATAC-seq, MNase-seq, and any other high-throughput sequencing that produces BAM or bigWig files.

Does it provide quality control for ChIP-seq?

Absolutely. It includes specific tools like plotFingerprint to assess enrichment strength and plotCorrelation to check replicate consistency.

deepTools NGS Analysis

Name: deepTools NGS Analysis
Author: jimmc414

byjimmc414

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324

数据科学与机器学习

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

关于

deepTools is a comprehensive suite of Python-based utilities optimized for Next-Generation Sequencing (NGS) data analysis. This skill empowers Claude to perform complex bioinformatics tasks such as normalizing BAM files into bigWig coverage tracks, conducting quality control via PCA and correlation analysis, and generating sophisticated heatmaps around genomic features. It is an essential tool for researchers working with ChIP-seq, RNA-seq, and ATAC-seq who require automated, reproducible workflows for autonomous discovery and data visualization.

主要功能

Comprehensive QC tools for PCA, correlation, and fingerprint analysis
Specialized workflows for ChIP-seq, RNA-seq, and ATAC-seq data
High-performance parallel processing for large-scale genomic files
Normalized coverage track generation (RPGC, CPM, RPKM, BPM)
324 GitHub stars
Advanced genomic visualization including heatmaps and profile plots

使用场景

Visualizing signal density at Transcription Start Sites (TSS) or specific peak regions
Validating the reproducibility of biological replicates through correlation matrices
Normalizing and comparing ChIP-seq signal enrichment between treatment and control groups

关于

主要功能

Comprehensive QC tools for PCA, correlation, and fingerprint analysis
Specialized workflows for ChIP-seq, RNA-seq, and ATAC-seq data
High-performance parallel processing for large-scale genomic files
Normalized coverage track generation (RPGC, CPM, RPKM, BPM)
324 GitHub stars
Advanced genomic visualization including heatmaps and profile plots

使用场景

Visualizing signal density at Transcription Start Sites (TSS) or specific peak regions
Validating the reproducibility of biological replicates through correlation matrices
Normalizing and comparing ChIP-seq signal enrichment between treatment and control groups