MiDAS-Meaningful Immunogenetic Data at Scale.

Area of Science:

• Immunogenetics
• Computational Biology
• Statistical Genetics

Background:

• Human immunogenetic variation, specifically HLA and KIR types, is linked to immune phenotypes.
• Current association studies often use limited analyses of HLA allelic diversity, hindering interpretability and reproducibility.

Purpose of the Study:

• To introduce MiDAS, a comprehensive R package for transforming and analyzing immunogenetic data.
• To facilitate advanced analyses including amino acid fine mapping, evolutionary divergence, and HLA-KIR interactions.
• To enable robust statistical association analyses with diverse phenotypes.

Main Methods:

• Development of the MiDAS R package.
• Recoding of HLA and KIR data into biologically meaningful variables.
• Implementation of statistical association analysis workflows for various phenotype scales.

Main Results:

• MiDAS provides a framework for detailed immunogenetic analysis.
• The package supports fine mapping of HLA amino acids and analysis of HLA-KIR interactions.
• MiDAS facilitates comprehensive statistical association studies.

Conclusions:

• MiDAS bridges the gap between immunogenetic data inference and discovery in immune and disease biology.
• The R package enhances the interpretability and reproducibility of immunogenetic association studies.
• MiDAS is freely available, promoting wider research application.