从 RNA-Seq 序列读取中进行 HLA 分型。
HLA typing from RNA-Seq sequence reads.
机构信息
TRON - Translational Oncology at the University Medical Center of the Johannes Gutenberg University, Langenbeckstrasse 1, Building 708, 55131 Mainz, Germany ; University Medical Center of the Johannes Gutenberg University Mainz, III, Medical Department, Langenbeckstrasse 1, 55131 Mainz, Germany.
TRON - Translational Oncology at the University Medical Center of the Johannes Gutenberg University, Langenbeckstrasse 1, Building 708, 55131 Mainz, Germany.
出版信息
Genome Med. 2012 Dec 22;4(12):102. doi: 10.1186/gm403. eCollection 2012.
We present a method, seq2HLA, for obtaining an individual's human leukocyte antigen (HLA) class I and II type and expression using standard next generation sequencing RNA-Seq data. RNA-Seq reads are mapped against a reference database of HLA alleles, and HLA type, confidence score and locus-specific expression level are determined. We successfully applied seq2HLA to 50 individuals included in the HapMap project, yielding 100% specificity and 94% sensitivity at a P-value of 0.1 for two-digit HLA types. We determined HLA type and expression for previously un-typed Illumina Body Map tissues and a cohort of Korean patients with lung cancer. Because the algorithm uses standard RNA-Seq reads and requires no change to laboratory protocols, it can be used for both existing datasets and future studies, thus adding a new dimension for HLA typing and biomarker studies.
我们提出了一种方法 seq2HLA，可使用标准的下一代测序 RNA-Seq 数据获得个体的人类白细胞抗原 (HLA) Ⅰ类和Ⅱ类类型和表达。将 RNA-Seq 读数映射到 HLA 等位基因的参考数据库上，并确定 HLA 类型、置信分数和基因座特异性表达水平。我们成功地将 seq2HLA 应用于 HapMap 项目中的 50 个人，在 P 值为 0.1 时，两位数字 HLA 类型的特异性为 100%，灵敏度为 94%。我们确定了之前未分型的 Illumina Body Map 组织以及一批韩国肺癌患者的 HLA 类型和表达。由于该算法使用标准的 RNA-Seq 读数，且不需要改变实验室方案，因此它可以用于现有数据集和未来的研究，从而为 HLA 分型和生物标志物研究增加了一个新的维度。
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