bio-rna-quantification-count-matrix-qc

What problem does it solve?

This Skill addresses the critical need for quality control of RNA-seq count matrices before downstream differential expression analysis, helping to identify and mitigate potential issues that could skew results.

Core Features & Use Cases

• Data Inspection: Load and inspect raw count data and sample metadata.
• Quality Metrics: Calculate basic statistics, filter low-count genes, and normalize data for visualization.
• Visualization: Generate heatmaps for sample correlation and PCA plots to assess sample relationships and batch effects.
• Outlier Detection: Identify potential outlier samples based on QC metrics.
• Use Case: Before running DESeq2 for differential expression, use this Skill to confirm that biological replicates cluster together, that there are no obvious batch effects, and that no samples are extreme outliers.

Quick Start

Run quality control on my RNA-seq count matrix to check for outliers and batch effects.