PIA - Protein Inference Algorithms
PIA is a toolbox for MS based protein inference and identification analysis.
PIA allows you to inspect the results of common proteomics spectrum identification search engines, combine them seamlessly and conduct statistical analyses. The main focus of PIA lays on the integrated inference algorithms, i.e. concluding the proteins from a set of identified spectra. But it also allows you to inspect your peptide spectrum matches, calculate FDR values across different search engine results and visualize the correspondence between PSMs, peptides and proteins.
PIA in a nutshell
Most search engines for protein identification in MS/MS experiments return protein lists, although the actual search yields a set of peptide spectrum matches (PSMs). The step from PSMs to proteins is called “protein inference”. If a set of identified PSMs supports the detection of more than one protein in the searched database (“protein ambiguity”), usually only one representative accession is reported. These representatives may differ according to the used search engine and settings. Thus, the protein lists of different search engines generally cannot be compared with one another. PSMs of complementary search engines are often combined to enhance the number of reported proteins or to verify the evidence of a peptide, which is improved by detection with distinct algorithms.
The tutorial as PDF can be downloaded here, the required data are available here and the workflows here (all data is also available in the tutorial repository at https://github.com/julianu/pia-tutorial/).
For further documentation please refer to the Wiki (https://github.com/mpc-bioinformatics/pia/wiki) on github.
Problems, Bugs and Issues
If you have any problems with PIA or find bugs and other issues, please use the issue tracker of github (https://github.com/mpc-bioinformatics/pia/issues).
Citation and Publication
If you found PIA useful for your work, please cite the following publications:
Authors of PIA
The programming work on PIA was performed by Julian Uszkoreit (Ruhr University Bochum, Medizinisches Proteom-Center), and Yasset Perez-Riverol (European Bioinformatics Institute (EMBL-EBI), Cambridge)