PIA - Protein Inference Algorithms
PIA is a toolbox for mass spectrometry-based protein inference and identification analysis. It enables users to inspect and combine results from common proteomics spectrum identification search engines and perform statistical analyses across datasets. A major focus of PIA lies in integrated protein inference algorithms that derive protein-level conclusions from identified spectra. In addition, PIA supports inspection of peptide-spectrum matches (PSMs), false discovery rate (FDR) calculation across multiple search engine outputs, and visualization of relationships between PSMs, peptides, and proteins.
Key benefits
Integrated toolbox for protein inference and identification analysis
Supports multiple proteomics search engine outputs
Combines and compares search engine results seamlessly
Protein inference algorithms for robust protein-level interpretation
FDR calculation and statistical analysis across datasets
Visualization of PSM–peptide–protein relationships
Applications
Protein inference from tandem mass spectrometry data
Inspection and comparison of peptide-spectrum matches
Integration of multiple search engine identification results
False discovery rate estimation and quality assessment
Visualization and interpretation of proteomics identifications
Intended use
PIA is intended for proteomics researchers, bioinformaticians, and mass spectrometry users who require robust tools for protein inference, statistical validation, and interpretation of proteomics identification results. It is particularly suited for workflows integrating multiple search engine outputs.
Contact:
Website