pXg: Comprehensive and Reliable Identification of MHC-I Antigens Using De Novo Peptide Sequencing and Immunotranscriptomic Datasets
peer-reviewed · Methods in Molecular Biology · 2026
| Date | 2026-10-16 |
| Type | peer-reviewed |
| Venue | Methods in Molecular Biology |
| Publisher | Springer US |
| Contribution | downstream-application |
| DOI | 10.1007/978-1-0716-5519-1_16 |
| Venue 2-year citedness | 1.14 |
Abstract
De novo peptide sequencing enables the identification of a broad repertoire of major histocompatibility complex class I-associated peptides, providing a valuable source of potential immunotherapeutic targets in cancer. Nevertheless, its practical utility remains limited by the absence of robust methods for confidently determining peptide-spectrum matches and interpreting their proteogenomic information. This chapter presents the pXg workflow, designed to comprehensively and reliably identify peptides derived from de novo sequencing in mass spectrometry-based immunopeptidomics, integrated with matched RNA-seq data. We guide the reader through the use of pXg, covering the rescoring of peptide-spectrum matches and the estimation of a false discovery rate from the popular de novo sequencing tool Casanovo. This ultimately yields rich proteogenomic insights into the identified peptides.
Methods and tools
- pXg: MHC-I noncanonical peptides
Methods it uses
- Casanovo: First Transformer