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PepPre

PepPre: Promote Peptide Identification Using Accurate and Comprehensive Precursors

Abstract

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Accurate and comprehensive peptide precursor ions are crucial to tandem mass spectrometry-based peptide identification. An identification engine can greatly benefit from the search space reduction hinted by credible and detailed precursors. Additionally, both the number of identifications and the spectrum explainability can be increased by considering multiple precursors per spectrum. Here, we propose PepPre, which detects precursors by decomposing peaks into multiple isotope clusters using linear programming methods. The detected precursors are scored and ranked, and the high-scoring ones are used for the following peptide identification. PepPre is evaluated both on regular and cross-linked peptides datasets, and compared with 11 methods in this paper. The experimental results show that PepPre achieves 203% more PSM and 68% more peptide identifications than instrument software for regular peptides, and 99% more PSM and 27% more peptide pair identifications for cross-linked peptides, which also outperforms all other evaluated methods. In addition to the increased identification numbers, further credibility evaluation evidence that the identifications are credible. Moreover, by widening the isolation window of data acquisition from 2 Th to 8 Th, the engine is able to identify at least 64% more PSMs with PepPre, demonstrating the potential advantages of large isolation windows.

Usage

Release

ui

PepPre 1.2.0

Linux | macOS (pkg) | macOS (zip) | Windows
Note:
  1. improved UI.

PepPre 1.1.1

Linux | macOS (pkg) | macOS (zip) | Windows
Note:
  1. change path for saving configuration.

PepPre 1.1.0

Linux | macOS | Windows
Note:
  1. embed `PepPepView` which can display deisotoped precursor ions and corresponding identification.
  2. adjust arguments of CLI interface.

PepPre 1.0.3

Note:
  1. the version is not publicly released.
  2. internal changes.
  3. adjust file type filtering of input data.
  4. adjust ext of output file: export as `{file_name}.precursor.[csv|tsv]` if `csv` or `tsv` is selected.

PepPre 1.0.2

Linux | macOS | Windows
Note:
  1. internal changes.
  2. show logo in ui.

PepPre 1.0.1

Linux | macOS | Windows
Note:
  1. internal changes.
  2. fix input file type detection.

PepPre 1.0.0

Linux | macOS | Windows

Q&A

Source

Example Data

Citation

BibTeX

@article{Tarn2023PepPre,
    author = {Ching Tarn and Yu-Zhuo Wu and Kai-Fei Wang},
    title = {PepPre: Promote Peptide Identification Using Accurate and Comprehensive Precursors},
    year = {2023},
    doi = {10.1101/2023.05.13.540645},
    publisher = {Cold Spring Harbor Laboratory},
    URL = {https://www.biorxiv.org/content/early/2023/05/14/2023.05.13.540645},
    eprint = {https://www.biorxiv.org/content/early/2023/05/14/2023.05.13.540645.full.pdf},
    journal = {bioRxiv}
}

APA

Tarn, C., Wu, Y.-Z., & Wang, K.-F. (2023). PepPre: Promote Peptide Identification Using Accurate and Comprehensive Precursors. bioRxiv, 2023.2005.2013.540645. https://doi.org/10.1101/2023.05.13.540645