FuFiHLA: a tool for full-field HLA typing from long-read data

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Authors: Jingqing Hu, Qian Qin, Heng Li, Ying Zhou
Cited by: 0
References: 17

Abstract

MOTIVATION: Allele typing for Human Leukocyte Antigen (HLA) genes has many important clinical applications. Popular short-read typing can only accurately distinguish alleles at the coding sequence level, which potentially limit our understanding of the effect of variants in non-coding region. Long read data has been proved to be useful in typing HLA alleles in full resolution, but only a few tools are publicly available and with significant limitations in practical application. RESULTS: We 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 233 PacBio HiFi WGS samples from HPRC shows that FuFiHLA achieves 99.6% accuracy in the full field allele typing and QV as 51.8 for consensus allele sequence construction. Additional testing on four Nanopore R10 reads demonstrates slightly reduced accuracy in the fourth field. AVAILABILITY: FuFiHLA is available at https://github.com/jingqing-hu/FuFiHLA under MIT License.

Fields of Study & Subjects

vaccines and immunoinformatics approaches T-cell and B-cell Immunology Advanced Biosensing Techniques and Applications

Publication details

Journal / source
Bioinformatics
Volume
42
Issue
5
Publication date
1 May 2026
Language
EN