Abstract 2582: KIRnome: KIR genotyping for whole genome/exome sequencing data

Abstract

Abstract In this study, we tried to develop valid KIR calling algorithm from WES/WGS data. As a consequence, here we suggest KIRnome (KIR typing for whole genome and exome sequencing) which is a KIR typing method for applying sequencing data such as WES/WGS. A total of 71 sequencing data (18 WES and 53 WGS data, respectively) and matched experimentally validated KIR genotype data are used to train and validate. Before developing this method, two types of allele references (genomic and coding, here after called gSeq and cSeq) are constructed by allele sequence of IPD/KIR. KIRnome consists of two part, first part is calculating normalized depth (here after called depth) of 16 KIR genes and considering allele reference length and second is estimating KIR type based on depth. In general, we get higher normalized depth when using genomic references for WGS data and using coding references for WES data. This coincides with scheme KIRnome and the characteristics of WGS and WES data. Given 71 samples of 3 data sets, we evaluated KIR genotyping performance of KIRnome per each KIR gene. For all 16 KIR genes, KIRnome shows >=98.5% accuracy. When KIRnome performance was tested only in 13 WES samples, the accuracy slightly drops to 94%. We assume this is attributable to relatively small number of the samples. In conclusion, we developed a novel and unique method named KIRnome for KIR typing from NGS data. KIRnome could determine KIR genotype accurately from WES and WGS data respectively. We expect KIRnome would facilitate revealation of immunogenetic facts in various disease. Moreover, future generation of KIR specific NGS data and improved reference sequence information of KIR would enable KIRnome to type KIR at allele level in a near future. Citation Format: Daeyoon Kim, Sung-Soo Yoon, Youngil Koh, Su Yeon Lee, Hongseok Yun, Sunghoon Cho, Hyung-Lae Kim. KIRnome: KIR genotyping for whole genome/exome sequencing data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2582. doi:10.1158/1538-7445.AM2017-2582