Prediction of HLA genotypes using NGS data

High-precision human leukocyte antigen (HLA) genotyping is crucial for anti-cancer immunotherapy, but existing tools predicting HLA genotypes using next-generation sequencing (NGS) data are insufficiently accurate.

Type: Other
Archiver: European Genome-Phenome Archive (EGA)

1 Dataset 1 Publication

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID	Description	Technology	Samples
EGAD00001007733	High-precision human leukocyte antigen (HLA) genotyping is crucial for anti-cancer immunotherapy, but existing tools predicting HLA genotypes using next-generation sequencing (NGS) data are insufficiently accurate. We compared the availability and accuracy of eight HLA genotyping tools (OptiType, HLA-HD, PHLAT, seq2HLA, arcasHLA, HLAscan, HLA*LA, and Kourami) using 1,275 cases from the 1000 Genomes Project data and created a new HLA-genotyping algorithm combining tools. Then, we assessed the new algorithm’s performance in 39 in-house samples with normal whole-exome sequencing (WES) data and polymerase chain reaction–sequencing-based typing (PCR-SBT) results.	Illumina HiSeq 2500	39

Publications	Citations
A New Human Leukocyte Antigen Typing Algorithm Combined With Currently Available Genotyping Tools Based on Next-Generation Sequencing Data and Guidelines to Select the Most Likely Human Leukocyte Antigen Genotype. Lee M, Seo JH, Song S, Song IH, Kim SY, Kim YA, Gong G, Kim JE, Lee HJ. Front Immunol 12: 2021 688183	9