ALPHLARD-NT: Bayesian Method for Human Leukocyte Antigen Genotyping and Mutation Calling through Simultaneous Analysis of Normal and Tumor Whole-Genome Sequence Data

Journal of computational biology

article

HayashiShuto¹  MoriyamaTakuya¹  YamaguchiRui¹  MizunoShinichi²  KomuraMitsuhiro¹  MiyanoSatoru¹  NakagawaHidewaki³  ImotoSeiya⁴ 

[1] Human Genome Center, The Institute of Medical Science, The University of Tokyo;Department of Health Sciences, Faculty of Medical Sciences, Kyushu University;RIKEN Center for Integrative Medical Sciences;Health Intelligence Center, The Institute of Medical Science, The University of Tokyo

关键词: Bayesian model;    HLA genotyping;    HLA mutation calling;    whole-exome sequencing;    whole-genome sequencing;   

DOI  :  10.1089/cmb.2018.0224

来源: Mary Ann Liebert, Inc. Publishers

【 摘 要 】

Human leukocyte antigen (HLA) genes provide useful information on the relationship between cancer and the immune system. Despite the ease of obtaining these data through nextgeneration sequencing methods, interpretation of these relationships remains challenging owing to the complexity of HLA genes. To resolve this issue, we developed a Bayesian method, ALPHLARD-NT, to identify HLA germline and somatic mutations as well as HLA genotypes from whole-exome sequencing (WES) and whole-genome sequencing (WGS) data. ALPHLARD-NT showed 99.2% accuracy for WGS-based HLA genotyping and detected five HLA somatic mutations in 25 colon cancer cases. In addition, ALPHLARD-NT identified 88 HLA somatic mutations, including recurrent mutations and a novel HLA-B type, from WES data of 343 colon adenocarcinoma cases. These results demonstrate the potential of ALPHLARD-NT for conducting an accurate analysis of HLA genes even from lowcoverage data sets. This method can become an essential tool for comprehensive analyses of HLA genes from WES and WGS data, helping to advance understanding of immune regulation in cancer as well as providing guidance for novel immunotherapy strategies.

【 授权许可】

Unknown