MHCcluster

MHCcluster performs functional clustering of MHC class I molecules based on predicted peptide binding specificities to delineate the functional diversity among HLA alleles.

Key Features:

• Predicted binding specificity: Uses predicted peptide binding specificities as the core criterion for assessing functional relationships among MHC class I molecules.
• Static heat map visualization: Summarizes pairwise functional relationships among MHC variants as a static heat map.
• Graphical tree-based visualizations: Illustrates hierarchical clustering of MHC molecules based on predicted binding specificity.
• Supertype identification: Identifies 12 major specificity groups (supertypes) among prevalent HLA-A and HLA-B alleles and highlights HLA molecules that do not fit existing supertypes.
• Cross-species analysis: Enables comparative analysis showing reduced functional diversity in chimpanzee MHC class I molecules relative to human HLA class I molecules.
• Support for human and nonhuman MHC data: Applies the same functional clustering approach to MHC molecules from human and nonhuman species.

Scientific Applications:

• T cell immunity research: Enables analysis of peptide binding capabilities of diverse MHC alleles to inform studies of T cell immune responses.
• Antigen presentation and immune recognition: Aids investigation of the molecular basis of antigen presentation and differences in immune recognition among alleles.
• Immunogenetics and comparative immunogenomics: Supports cross-species comparisons of MHC functional diversity, including human versus chimpanzee analyses.

Methodology:

Clustering is performed on predicted peptide binding specificities with hierarchical clustering and results are summarized as static heat maps and tree-based visualizations.