PTM-Invariant Peptide Identification


About PIPI

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.

The performance of PIPI

Simulation experiments: (Spectra data (MGF) and database (fasta): sim.zip)


Standard protein mixture experiments:


24 real data experiments:


Running time:

The average running time of analyzing one data set. The unit is hour.

The running time of MS-Alignment and ProteinProspector is marked with an "*" for analyzing human samples. This indicates that they used a custom database that is much smaller than the database used by other tools.

Where to download PIPI and how to use it?

Executable file can be downloaded from: https://github.com/fcyu/PIPI/releases (Downloads = ).

Source code: https://github.com/fcyu/PIPI (Visits = ).

Bug or issue report: https://github.com/fcyu/PIPI/issues

Requirement: With Percolator Installed. Java version >= 1.7.

Usage:

java -Xmx25g -jar PIPI.jar parameter.def spectra_file

parameter.def: Parameter file. Can be download along with PIPI.

spectra_file: Spectra data file (mzXML).

For any enquiry, please contact Fengchao YU at fyuab@connect.ust.hk

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]