bioRxivBioinformaticsPreprint
Integration of HLA-DR linkagedisequilibrium to MHC class II predictions
Mette Bøge Pedersen, Sarah Rosenberg Asmussen, Freja Malou Sarfelt, Astrid Brix SaksageriD, Peter Wad SackettiD, Morten NielseniD, Carolina BarraiD
- Citations
- 5
Abstract
Insights into peptide binding to HLA class II molecules is essential when studying the biological mechanisms behind cellular immunity, autoimmune diseases, and the development of immunotherapies and peptide vaccines. Currently, most of the publicly available data used to train state-of-the-art binding prediction methods for HLA-DR only includes DRB1 information. The role of the paralogue alleles, HLA-DRB3/4/5, and their strong linkage disequilibrium to DRB1 is often omitted when typing HLA-II alleles. This leads to ambiguities when making disease associations and interpreting HLA-restricted immune data. To resolve this issue, we present HLAAssoc-1.0, a method to infer HLA-DRB3/4/5 alleles by linkage disequilibrium to HLA-DRB1. We illustrate the usage of the tool and the importance of the integration of HLA-DRB3/4/5 alleles in the data analysis in different case studies including the interpretation of immunopetidomics data. Additionally, we infer allele information for the data used for training of NetMHCIIpan lacking HLA-DRB3/4/5 allele information and demonstrate that the retrained method achieved improved performance. In all cases, inferring HLA-DRB3/4/5 allele presence in non-fully typed HLA-II assays resulted in improved allele and motif deconvolutions. HLAAssoc-1.0 is available at https://services.healthtech.dtu.dk/service.php?HLAAssoc-1.0.
- organism: human
- assay: proteomics
- research focus: deconvolution
- research focus: benchmarking
- research focus: software / tool
- approach: statistical model
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