To accurately characterize the neo-antigen repertoire in tumors, identifying the HLA alleles of the patient is paramount. The binding of the neo-antigens to the patient's specific HLA alleles HLA-restriction has to be determined to identify neo-antigens that might play a role in stimulating an immune response in immunotherapy. The information on the patient's HLA alleles is captured in the next-generation sequencing (NGS) data and has to be accurately teased out using in-silico HLA typing software. However, to our knowledge, until now an independent study of HLA typing software has not been carried out. In this study, five publicly available HLA typing software packages were compared using 106 whole exome sequencing samples from the 1000 Genomes Project and a published dataset of 56 Asian nasopharyngeal tumor-normal pairs with experimentally determined HLA types. Whole exome sequencing samples of varying depth and coverage were chosen to simulate real-world data and test the robustness of the HLA typing software.

Citation Format: Alvin Ng, Steve Rozen. Independent comparison of the state of the art in-silico HLA typing software. [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2016 Oct 20-23; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2017;5(3 Suppl):Abstract nr B12.