1)陕西师范大学计算机科学学院,西安 710119;2)公安部物证鉴定中心,北京 100038;3)江苏师范大学,徐州 221116;4)安澜智能(深圳)有限公司,深圳 510630;5)中国政法大学,证据科学教育部重点实验室,北京 100088
This work was supported by grants from the National Science and Technology Resources Sharing Service Platform Project (YCZYPT[2017]01-3), the Fundamental Research Funds for Institute of Forensic Science (2019JB011, 2021JB004), the Key Research and Development Program of Shaanxi Province(2018SF-251), the Ministry of Public Security Double Ten Key Project (2019SSJH0601) and Beijing Leading Talent Project (Z18110006318006).
Objective To evaluate the accuracy of predicting the kinship relationship between individuals based on the identity-by-state (IBS) algorithm.Methods The Illumina GSA chip was used to perform whole-genome detection on 253 samples. Based on high-density single nucleotide polymorphism (SNP) data, the IBS sharing statistics between two individuals was calculated to predict the kinship relationship. Filtering SNP by different conditional parameters to evaluate the influence of the number of sites on the accuracy of the algorithm’s prediction.Results The prediction accuracy rate of 1st-4th degree of relatives proved to be as high as 99%, with a paired difference of 1st degree and no false positive. Decrease in the number of SNPs has no significant impact on the accuracy of prediction, and the algorithm still achieves a higher accuracy rate even in the lower density of SNP markers.Conclusion The IBS algorithm provides an effective method for forensic genealogy inference, which has good application value for forensic on-site inspection materials with trace degradation.
GUAN Shan-Shan, ZHANG Wen-Jie, WEI Yi-Liang, LI Ying-Xiang, ZHAO Wen-Ting, FAN Hong, LIU Jing. Accuracy Research on The Kinship Relationship Prediction by IBS Algorithm[J]. Progress in Biochemistry and Biophysics,2022,49(3):591-599
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