lib-deeptools

What problem does it solve?

This Skill simplifies complex Next-Generation Sequencing (NGS) data analysis, enabling users to efficiently process, visualize, and interpret genomic data from various experiments like ChIP-seq, RNA-seq, and ATAC-seq.

Core Features & Use Cases

• Data Conversion & Normalization: Convert BAM files to normalized bigWig tracks, essential for visualization and comparison.
• Quality Control: Perform comprehensive QC checks including sample correlation, PCA, and fingerprint analysis to ensure data reliability.
• Visualization: Generate publication-quality heatmaps and profile plots around genomic features (e.g., TSS, peaks).
• Use Case: Analyze ChIP-seq data by converting BAM files to bigWig, checking replicate correlation, and visualizing signal enrichment around known peak regions.

Quick Start

Use the lib-deeptools skill to convert a BAM file named 'sample.bam' into a normalized bigWig file named 'sample.bw' using RPGC normalization and an effective genome size of 2913022398.