proteomics-de

What problem does it solve?

This Skill automates the statistical testing required to identify proteins that show significant differences in abundance between experimental conditions, a crucial step in many proteomics studies.

Core Features & Use Cases

• Statistical Testing: Implements robust methods like MSstats, limma, proDA, and standard t-tests for differential abundance analysis.
• Multiple Testing Correction: Applies Benjamini-Hochberg FDR to control false discovery rates.
• Visualization: Generates volcano plots and heatmaps to visualize results.
• Use Case: After performing a mass spectrometry experiment comparing treated vs. control samples, use this Skill to pinpoint which proteins are significantly up or down-regulated.

Quick Start

Run differential abundance testing on the provided protein matrix using the limma method.