PXD056915

PXD056915 is an original dataset announced via ProteomeXchange.

Title	PeptideForest: Semi-supervised machine learning integrating multiple search engines for peptide identification
Description	We introduce PeptideForest, a semi-supervised machine learning approach that integrates the assignment of peptides to mass spectra from multiple algorithms to train a random forest classifier, thereby combining the results from different search engines. PeptideForest increases the number of peptide-to-spectrum matches that exhibit a q-value lower than 1% by 25.2 ± 1.6% compared to MS-GF+ data on samples containing mixed HEK and Escherichia coli proteomes. However, an increase in quantity does not necessarily reflect an increase in quality and this is why we devised a novel approach to determine the quality of the assigned spectra through TMT quantification of samples with known ground truths. Thereby, we could show that the increase in PSMs below 1% q-value does not come with a decrease in quantification quality and as such PeptideForest offers a possibility to gain deeper insights into bottom-up proteomics. PeptideForest has been integrated into our pipeline framework Ursgal and can therefore be combined with a wide array of algorithms.
HostingRepository	PRIDE
AnnounceDate	2025-06-02
AnnouncementXML	Submission_2025-06-02_15:06:56.058.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Stefan Schulze
SpeciesList	scientific name: Escherichia coli; NCBI TaxID: 562; scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	TMT6plex-126 reporter+balance reagent acylated residue; iodoacetamide derivatized residue
Instrument	Q Exactive HF

Revision	Datetime	Status	ChangeLog Entry
0	2024-10-17 11:44:11	ID requested
⏵ 1	2025-06-02 15:06:56	announced

10.1021/acs.jproteome.4c00686;

Ranff T, Dennison M, B, é, dorf J, Schulze S, Zinn N, Bantscheff M, van Heugten JJRM, Fufezan C, PeptideForest: Semisupervised Machine Learning Integrating Multiple Search Engines for Peptide Identification. J Proteome Res, 24(2):929-939(2025) [pubmed]

submitter keyword: Human, machine learning, E. coli, statistical post-processing, peptide identification

Christian Fufezan
contact affiliation	Cellzome A GSK Company, Heidelberg 69117, Germany
contact email	christian@fufezan.net
lab head
Stefan Schulze
contact affiliation	University of Pennsylvania
contact email	sschulze@sas.upenn.edu
dataset submitter

Dataset FTP location NOTE: Most web browsers have now discontinued native support for FTP access within the browser window. But you can usually install another FTP app (we recommend FileZilla) and configure your browser to launch the external application when you click on this FTP link. Or otherwise, launch an app that supports FTP (like FileZilla) and use this address: ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2025/06/PXD056915

PRIDE project URI

• PRIDE
  1. PXD056915
     1. Label: PRIDE project
     2. Name: PeptideForest: Semi-supervised machine learning integrating multiple search engines for peptide identification