KRSA

KRSA analyzes kinome peptide array data to infer differential kinase activities and phosphorylation signatures for serine-threonine and tyrosine kinases.

Key Features:

• End-to-End Analysis Workflow: Performs data reading, formatting, model fitting, statistical analysis, and visualization for kinome peptide array datasets.
• High-Throughput Data Handling: Handles high-throughput, multi-dimensional peptide array data from platforms such as PamStation12 (PamGene).
• Model Fitting and Analysis: Applies validated model-fitting algorithms to identify active kinases and infer kinase activity patterns.
• Visualization Capabilities: Produces graphical outputs representing differential phosphorylation and inferred kinase activities.
• Comparative Analysis: Compares current datasets with existing published datasets to corroborate findings.
• Implementation: Implemented as an R package for computational analysis of peptide array data.

Scientific Applications:

• Phosphorylation Landscape Analysis: Identifies differential phosphorylation signatures indicating variations in kinase activity across biological conditions.
• Comparative Kinome Studies: Detects sex-specific phosphorylation patterns and upstream kinase activities in dorsolateral prefrontal cortex (DLPFC) samples from male and female subjects and enables comparison with previously published datasets.

Methodology:

Performs data reading, formatting, model fitting, analysis, visualization, and dataset comparison on peptide array data using validated algorithms to infer kinase activity from peptide phosphorylation measurements.