Numerous statistical methods have been developed to explore genomic imprinting and maternal effects by identifying parent-of-origin patterns in complex human diseases. However, because most of these methods only use available locus-specific genotype data, it is sometimes impossible for them to infer the distribution of parental origin of a variant allele, especially when some genotypes are missing. In this article, we propose a two-step approach, LIMEhap, to improve upon a recent partial likelihood inference method. In the first step, the distribution of the missing genotypes is inferred through the construction of haplotypes by using information from nearby loci. In the second step, a partial likelihood method is applied to the inferred data. To substantiate the validity of the proposed procedures, we simulated data in a genomic region of gene GPX1. The results show that, by borrowing genetic information from nearby loci, the power of the proposed method can be close to that with complete genotype data at the locus of interest. Since the inference on the genotype distribution is made under the assumption of Hardy–Weinberg Equilibrium (HWE), we further studied the robustness of LIMEhap to violation of HWE. Finally, we demonstrate the utility of LIMEhap by applying it to an autism dataset.
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The authors would like to thank the Section Editor and the anonymous reviewers for their constructive comments and suggestions, which, in our view, have led to improved presentation and greater clarity. The autism spectrum disorder family data, made available by the AGP, were downloaded from dbGaP (Accession: phs000267.v1.p1).
This work was supported in part by the National Science Foundation grant DMS-1208968.
Conflict of interest
The authors declare that they have no conflict of interest.
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Zhang, F., Lin, S. Incorporating information from markers in LD with test locus for detecting imprinting and maternal effects. Eur J Hum Genet (2020). https://doi.org/10.1038/s41431-020-0590-3