MHC-TP

Cluster immunopeptidomics peptides by their HLA/MHC binding motif and get a ranked table plus a standalone interactive HTML report.

mhc-tp takes a GibbsCluster output folder, correlates each cluster's position-specific scoring matrix against a reference of HLA/MHC class I + II binding motifs (human & mouse), and writes the best allele match per cluster.

Get started View an example report

Install

git clone https://github.com/PurcellLab/MHC-TP.git
cd MHC-TP
pip install -e .

Then fetch the reference motifs (once) and run a search:

mhc-tp fetch -s human
mhc-tp search <gibbscluster_output_dir> -s human -o results/

See the Usage guide for all options and the API reference for the search engine internals (including the correlation maths).

How it works

For each GibbsCluster motif, every reference allotype motif is scored by the Pearson correlation of their flattened position-weight matrices, computed only over the informative cells of the cluster motif. Per cluster the allotypes are ranked by this correlation (PCC); see mhc_tp.engine.search for the full method.

Citation

If you use MHC-TP, please cite:

Munday PR, Krishna SSG, Fehring J, Croft NP, Purcell AW, Li C, Braun A. Immunolyser 2.0: An advanced computational pipeline for comprehensive analysis of immunopeptidomic data. Comput Struct Biotechnol J. 2025;29:296–304. doi:10.1016/j.csbj.2025.10.007.