StatsPro

StatsPro integrates and evaluates statistical methods to detect differentially expressed proteins (DEPs) in label-free quantitative proteomics.

Key Features:

• Integration of Statistical Approaches: Incorporates 12 common testing algorithms and 6 P-value combination methods for DEP detection.
• Effect Size Calculation: Calculates Cohen's d effect size for every protein.
• Performance Evaluation Criteria: Assesses method performance using the number of DEPs identified; the correlation coefficient between P-values and effect sizes; and the Area under the ROC curve (AUC).
• Case Studies with Acquisition Modes: Demonstrates application on two label-free quantitative proteomics case studies using data-dependent acquisition (DDA) and data-independent acquisition (DIA).

Scientific Applications:

• LC-MS label-free quantitative proteomics: Supports analysis of LC-MS–based label-free quantitative proteomics datasets for DEP detection.
• Method benchmarking across acquisition types: Enables benchmarking and selection of statistical methods for identifying DEPs across different experimental conditions and acquisition modes (DDA and DIA).

Methodology:

Organizes multiple testing algorithms and P-value combination strategies, computes Cohen's d effect sizes per protein, and evaluates methods using number of DEPs, P-value–effect size correlation, and AUC.