Accuracy Research on The Distant Kinship Relationship Prediction by IBD Algorithm

Objective To construct an analysis process for identity-by-descent (IBD) algorithm to predict distant relatives and evaluate the prediction accuracy. Methods 253 family samples were detected by using high density whole genome single nucleotide polymorphism (SNP) chip. IBD algorithm was used to predict the genetic relationship between pairs of individuals, and the prediction accuracy was evaluated. The number of SNPs was randomly reduced to evaluate the effect of SNP numbers on the accuracy of the algorithm prediction. Results Among 1-7th kinship degree, the average confidence interval accuracy of IBD algorithm was 94.72%, and the prediction credibility was 99.77%. The false negative of IBD algorithm was found when kinship degree is 6 or higher. When the number of SNPs decreases, the prediction accuracy will decline to a certain extent. Conclusion The IBD algorithm can accurately predict the genetic relationship within the seventh kinship degree, and it has important application value in population genetics, forensic genealogy inference and other fields.