Welcome to PepQuery

PepQuery is a peptide-centric search engine for novel peptide identification and validation. Cancer genomics studies have identified a large number of genomic alterations that may lead to novel, cancer-specific protein sequences. Proteins resulted from these genomic alterations are attractive candidates for cancer biomarkers and therapeutic targets. The leading approach to proteomic validation of genomic alterations is to analyze tandem mass spectrometry (MS/MS) data using customized proteomics databases created from genomics data. Such analysis is time-consuming and requires thorough training and detailed knowledge in proteomics data analysis, leading to a gap between MS/MS data and the cancer genomics community. PepQuery does not require customized databases and allows quick and easy proteomic validation of genomic alterations. Learn More

PepQuery Online

Server 1:
Search your peptide against large public cancer datasets with the web interface of PepQuery.

Server 2:
Search your peptide against CPTAC proteomics data using PDC PepQuery Online.


PepQuery Standalone

Using PepQuery standalone version for your own data.


  1. Released PepQuery version 1.4.1. In this version, we supported MHC ligand identification using immunopeptidomics data and fixed a few bugs.
  1. Released PepQuery version 1.2.0.
  1. Added a tool to support searching multiple datasets in a single run.
  1. Added more than 30 MS/MS datasets for the web server. This increased the total number of MS/MS spectra more than 0.5 billion;
  2. Updated PepQuery to output the best matches from the reference database searching for the spectra which matched to the input target peptides;
  3. Updated web server of PepQuery to present the best matched annotated spectra from the reference database searching.
  1. Updated protein reference database for dataset PASS00215_jurcat in the web server.

How to Cite
Wen, Bo, Xiaojing Wang, and Bing Zhang. "PepQuery enables fast, accurate, and convenient proteomic validation of novel genomic alterations." Genome research 29.3 (2019): 485-493.
Wen, Bo, Kai Li, Yun Zhang, and Bing Zhang. "Cancer neoantigen prioritization through sensitive and reliable proteogenomics analysis." Nature communications 11.1 (2020): 1-14.

If you have any questions, suggestions or remarks, please open an issue at Github issues tracker or reach us through Gitter or PepQuery Google Group.