SOFTWARE
MHCBooster is an AI-powered tool that leverages deep learning models to enhance immunopeptide identification. By providing reliability measurements across key dimensions like retention time (RT), MS2, ion mobility (IM), and antigen processing and presentation (APP) for both MHC-I and MHC-II peptides, MHCBooster increases the sensitivity and specificity in epitope identifications, especially in lower-input scenarios. MHCBooster features a graphical user interface and is also available via command line or as a Python package.
MhcValidator is a deep learning-powered tool designed to identify peptide-spectrum matches in mass spectrometry-based immunopeptidomics. It combines database search metrics with MHC interaction and presentation predictors within its discriminant function.
MhcVizPipe
MhcVizPipe is a reporting pipeline designed for visualizing and performing quality control on immunopeptidomics mass spectrometry data. It enables quick assessment and comparison of sample quality and composition across single or multiple files. Common use cases include evaluating QC samples or comparing samples during method development.
RHybridFinder is an R package for processing immuno-peptidomics mass spectrometry data to discover putative hybrid peptides. It provides computational inference of potential proteasomal spliced peptides detected by mass spectrometry, making it ideal for researchers focused on identifying spliced peptides in their data.
