bio-clinical-databases-hla-typing

HLA typing from NGS data uses tools like OptiType, HLA-HD, or arcasHLA to call HLA-A, HLA-B, and HLA-C alleles from WES, WGS, or RNA-seq datasets. The parsed results provide standardized four-field alleles to support clinical transplant matching and pharmacogenomic screening.

Parsing OptiType and arcasHLA outputs involves standardizing raw allele calls into four-field HLA alleles. This tool-agnostic parsing workflow extracts HLA-A, HLA-B, and HLA-C results to generate standardized clinical reports for patient matching and drug-response screening.

HLA typing with OptiType fully supports RNA-seq data alongside WES and WGS datasets. You can run the workflow directly on RNA-seq reads to obtain accurate four-field HLA-A, HLA-B, and HLA-C calls for clinical reporting.

HLA typing workflows primarily call Class I loci (HLA-A, HLA-B, HLA-C) using OptiType. Calling Class II loci requires applying other specific tools like HLA-HD or arcasHLA to your WES, WGS, or RNA-seq data for broader immunogenomic profiling.

Four-field HLA alleles provide the high-resolution specificity required for accurate pharmacogenomic screening and transplant matching. Standardizing NGS calls to this resolution ensures precise identification of patient HLA types, minimizing graft rejection risks and adverse drug responses.