Abstract
HLA typing is crucial for clinical and research applications, including transplantation, disease association studies and personalised medicine. This study provides an in-depth analysis of five key challenges in computational HLA typing methods: varying lengths, high polymorphism, complex phylogenetic structures, high sequence similarity and the requirement for frequent updates. This study evaluates 27 computation-based HLA typing tools developed over the past 12 years, using a novel sequencing dataset of A549 cell lines with matched short-read RNA-Seq and long-read Iso-Seq data. We comprehensively investigated these 27 tools in terms of accessibility, capability, reliability, reproducibility, scalability and performance. In addition, we discuss the advantages and disadvantages of current tools and identify critical areas for future research and development to advance HLA typing technologies.