A New Genotype Imputation Method with Tolerance to High Missing Rate and Rare Variants

Yumei Yang, Qishan Wang, Qiang Chen, Rongrong Liao, Xiangzhe Zhang, Hongjie Yang, Youmin Zheng, Zhiwu Zhang and Yuchun Pan

PLOS ONE, 2014, vol. 9, issue 6, 1-7

Abstract: We report a novel algorithm, iBLUP, to impute missing genotypes by simultaneously and comprehensively using identity by descent and linkage disequilibrium information. The simulation studies showed that the algorithm exhibited drastically tolerance to high missing rate, especially for rare variants than other common imputation methods, e.g. BEAGLE and fastPHASE. At a missing rate of 70%, the accuracy of BEAGLE and fastPHASE dropped to 0.82 and 0.74 respectively while iBLUP retained an accuracy of 0.95. For minor allele, the accuracy of BEAGLE and fastPHASE decreased to −0.1 and 0.03, while iBLUP still had an accuracy of 0.61.We implemented the algorithm in a publicly available software package also named iBLUP. The application of iBLUP for processing real sequencing data in an outbred pig population was demonstrated.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0101025

DOI: 10.1371/journal.pone.0101025

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