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bioRxiv · 10.1101/2025.10.23.684216

FuFiHLA: A tool for Full-Field HLA typing from long read data

Hu, J.·Qin, Q.·Li, H.·Zhou, Y.
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Abstract

0.MotivationAllele typing for Human Leukocyte Antigen (HLA) genes has many important clinical applications. Popular short-read typing can only accurately distinguish alleles at the peptide level, which potentially limit our understanding of the effect of variants in non-coding region. Recently, a few methods were declared to distinguish full-field HLA alleles from de-novo assemblies, which motivates us to develop an accurate HLA typing method directly from long reads. ResultsWe developed FuFiHLA, a lightweight open-source software, to type HLA alleles. Currently it supports typing alleles of six HLA genes (HLA-A, HLA-B, HLA-C, HLA-DRB1, HLA-DQA1, and HLA-DQB1) from long reads. Evaluation using 47 PacBio HiFi samples from HPRC shows that FuFiHLA achieves 99.57% accuracy in the full field allele typing and QV as 50.1 for consensus allele sequence construction. Additional testing on four Nanopore R10 reads demonstrates slightly reduced accuracy in the fourth field. Availability and implementationFuFiHLA is available on GitHub (https://github.com/jingqing-hu/FuFiHLA) under MIT License.

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Hu, J., Qin, Q., Li, H., Zhou, Y.. 2025-10-24. FuFiHLA: A tool for Full-Field HLA typing from long read data. https://doi.org/10.1101/2025.10.23.684216

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