PTM-Invariant Peptide Identification
PIPI is short for PTM-Invariant Peptide Identification. It belongs to the category of unrestricted tools.
It first codes peptide sequences into Boolean vectors and codes experimental spectra into real-valued vectors. For each coded spectrum, it then searches the coded sequence database to find the top scored peptide sequences as candidates. After that, PIPI uses dynamic programming to localize and characterize modified amino acids in each candidate.
We used simulation experiments and real data experiments to evaluate the performance in comparison with restricted tools (i.e. Mascot, Comet, and MS-GF+) and unrestricted tools (i.e. Mascot with error tolerant search, MS-Alignment, ProteinProspector, and MODa). Comparison with restricted tools shows that PIPI has a close sensitivity and running speed. Comparison with unrestricted tools shows that PIPI has the highest sensitivity except for Mascot with error tolerant search and ProteinProspector. These two tools simplify the task by only considering up to 1 modified amino acid in each peptide, which results in a higher sensitivity but has difficulty in dealing with multiple modified amino acids. The simulation experiments also show that PIPI has the lowest false discovery proportion, the highest PTM characterization accuracy, and the shortest running time among the unrestricted tools.
|Where to download PIPI and how to use it?|
Executable file can be downloaded from: PIPI.zip (Downloads = ).
Source code: Available upon request.
Bug or issue report: email@example.com
Requirement: With Percolator Installed. Java version >= 1.8.
java -Xmx25g -jar PIPI.jar parameter.def spectra_file
parameter.def: Parameter file. Can be download along with PIPI.
For any enquiry, please contact Fengchao YU at firstname.lastname@example.org
Subscribe to PIPI's Google Group for announcements and questions.
|Related Publication (Submitted)|
|Fengchao Yu, Ning Li*, Weichuan Yu*. *Joint corresponding authors.
"PIPI: PTM-Invariant Peptide Identification Using Coding Method".
Journal of Proteome Research, 15(12): 4423-4435, 2016, [link]