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FuFiHLA: a tool for full-field HLA typing from long-read data.
Jingqing Hu1, Qian Qin1,2,3, Heng Li1,2,4
1Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02115, United States.
Bioinformatics (Oxford, England)
|May 5, 2026
Summary
FuFiHLA is a new open-source tool for high-resolution Human Leukocyte Antigen (HLA) typing using long-read sequencing data. It achieves 99.6% accuracy for six HLA genes, improving upon existing methods.
Area of Science:
- Genomics
- Immunogenetics
Background:
- Human Leukocyte Antigen (HLA) allele typing is crucial for clinical applications.
- Short-read sequencing has limitations in resolving non-coding variants.
- Existing long-read HLA typing tools have practical limitations.
Purpose of the Study:
- To develop a lightweight, open-source software for high-resolution HLA allele typing using long-read data.
- To address the limitations of current HLA typing tools.
Main Methods:
- Development of FuFiHLA, an open-source software tool.
- Utilized long-read sequencing data (PacBio HiFi and Nanopore R10).
- Supported typing for six key HLA genes (HLA-A, -B, -C, -DRB1, -DQA1, -DQB1).
Main Results:
- FuFiHLA achieved 99.6% accuracy for full-field allele typing on PacBio HiFi WGS data.
- Consensus allele sequence construction yielded a QV of 51.8.
- Slightly reduced accuracy in the fourth field was observed with Nanopore R10 reads.
Conclusions:
- FuFiHLA provides an accurate and efficient solution for HLA typing from long-read data.
- The tool supports typing of clinically relevant HLA genes with high resolution.
- FuFiHLA is available as open-source software for broader application.
