iPepGen: a modular, immunopeptidogenomic analysis pipeline for discovery, verification, and prioritization of cancer peptide neoantigen candidates

Characterizing tumor-specific neoantigen peptides, derived from genomic or transcriptomic aberrations and presented to the immune system, is critical for immuno-oncology studies. To this end, the modular iPepGen immunopeptidogenomics pipeline provides these functions: (1) Neoantigen prediction and protein database generation from genomic or transcriptomic sequencing data; (2) Peptide identification (3) Verification from immunopeptidomic mass spectral data; (4) Neoantigen classification and visualization; (5) Candidate prioritization for further study. Easy access via a publicly available, scalable cloud-based gateway coupled with online, interactive training materials streamlines the adoption by cancer researchers who require immunopeptidogenomic analysis tools but lack advanced computational expertise and resources.

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Publication Details

Journal
Genome biology
Published
2026-02-25
DOI
https://doi.org/10.1186/s13059-026-04012-2
Primary Topic
vaccines and immunoinformatics approaches
Type
article
Field-Weighted Citation Impact
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article

iPepGen: a modular, immunopeptidogenomic analysis pipeline for discovery, verification, and prioritization of cancer peptide neoantigen candidates

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Genome biology
vaccines and immunoinformatics approaches
article

iPepGen: a modular, immunopeptidogenomic analysis pipeline for discovery, verification, and prioritization of cancer peptide neoantigen candidates

Kyle A. Richards, Timothy J. Griffin, James R. Johnson, D A Largaespada, Reid Wagner, Pratik Dilip Jagtap, Flavia E. Popescu, Susan Coleman, Subina Mehta, Katherine Do, Tyler Jubenville, Alexey I. Nesvizhskii, Fengchao Yu
article en

Abstract

Characterizing tumor-specific neoantigen peptides, derived from genomic or transcriptomic aberrations and presented to the immune system, is critical for immuno-oncology studies. To this end, the modular iPepGen immunopeptidogenomics pipeline provides these functions: (1) Neoantigen prediction and protein database generation from genomic or transcriptomic sequencing data; (2) Peptide identification (3) Verification from immunopeptidomic mass spectral data; (4) Neoantigen classification and visualization; (5) Candidate prioritization for further study. Easy access via a publicly available, scalable cloud-based gateway coupled with online, interactive training materials streamlines the adoption by cancer researchers who require immunopeptidogenomic analysis tools but lack advanced computational expertise and resources.

Genome biology
University of Minnesota (US), University of Michigan (US), University of Minnesota Medical Center (US)
Partnerships for the goals
Openalex Percentile: Top 43%
vaccines and immunoinformatics approaches
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