Department of Oncology, The Second Xiangya Hospital of Central South University, Changsha, China.
The First Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, China.
Front Immunol. 2021 Mar 31;12:652258. doi: 10.3389/fimmu.2021.652258. eCollection 2021.
With the great progress made recently in next generation sequencing (NGS) technology, sequencing accuracy and throughput have increased, while the cost for data has decreased. Various human leukocyte antigen (HLA) typing algorithms and assays have been developed and have begun to be used in clinical practice. In this study, we compared the HLA typing performance of three HLA assays and seven NGS-based HLA algorithms and assessed the impact of sequencing depth and length on HLA typing accuracy based on 24 benchmarked samples. The algorithms HISAT-genotype and HLA-HD showed the highest accuracy at both the first field and the second field resolution, followed by HLAscan. Our internal capture-based HLA assay showed comparable performance with whole exome sequencing (WES). We found that the minimal depth was 100X for HISAT-genotype and HLA-HD to obtain more than 90% accuracy at the third field level. The top three algorithms were quite robust to the change of read length. Thus, we recommend using HISAT-genotype and HLA-HD for NGS-based HLA genotyping because of their higher accuracy and robustness to read length. We propose that a minimal sequence depth for obtaining more than 90% HLA typing accuracy at the third field level is 100X. Besides, targeting capture-based NGS HLA typing may be more suitable than WES in clinical practice due to its lower sequencing cost and higher HLA sequencing depth.
随着下一代测序(NGS)技术的最近取得的巨大进展,测序准确性和通量增加了,而数据成本降低了。各种人类白细胞抗原(HLA)分型算法和检测方法已经开发出来并开始应用于临床实践。在这项研究中,我们比较了三种 HLA 检测方法和七种基于 NGS 的 HLA 算法的 HLA 分型性能,并根据 24 个基准样本评估了测序深度和长度对 HLA 分型准确性的影响。算法 HISAT-genotype 和 HLA-HD 在第一字段和第二字段分辨率上均具有最高的准确性,其次是 HLAscan。我们内部的基于捕获的 HLA 检测方法与全外显子组测序(WES)具有可比的性能。我们发现,对于 HISAT-genotype 和 HLA-HD,最小深度为 100X,可在第三字段水平获得超过 90%的准确性。前三个算法对读取长度的变化非常稳健。因此,由于其更高的准确性和对读取长度的稳健性,我们建议使用 HISAT-genotype 和 HLA-HD 进行基于 NGS 的 HLA 基因分型。我们建议,获得第三字段水平 HLA 分型准确性超过 90%的最小序列深度为 100X。此外,由于其测序成本较低且 HLA 测序深度较高,基于靶向捕获的 NGS HLA 分型可能比 WES 更适合临床实践。