Evidence map›Paper›PMID 25189228›Full record

ArticleJournal of genetics2014

Detection of parent-of-origin effects for quantitative traits using general pedigree data.

Hai-Qiang He, Wei-Gao Mao, Dongdong Pan, Ji-Yuan Zhou, Ping-Yan Chen, Wing Kam Fung

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Article in Journal of genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Hai-Qiang HeDepartment of Biostatistics, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou 510515, People's Republic of China. zhoujiyuan@gmail.com.
Wei-Gao Mao
Dongdong Pan
Ji-Yuan Zhou
Ping-Yan Chen
Wing Kam Fung

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genomic imprinting is a genetic phenomenon in which certain alleles are differentially expressed in a parent-of-origin-specific manner, and plays an important role in the study of complex traits. For a diallelic marker locus in human, the parentalasymmetry tests Q-PAT(c) with any constant c were developed to detect parent-of-origin effects for quantitative traits. However, these methods can only be applied to deal with nuclear families and thus are not suitable for extended pedigrees. In this study, by making no assumption about the distribution of the quantitative trait, we first propose the pedigree parentalasymmetry tests Q-PPAT(c) with any constant c for quantitative traits to test for parent-of-origin effects based on nuclear families with complete information from general pedigree data, in the presence of association between marker alleles under study and quantitative traits. When there are any genotypes missing in pedigrees, we utilize Monte Carlo (MC) sampling and estimation and develop the Q-MCPPAT(c) statistics to test for parent-of-origin effects. Various simulation studies are conducted to assess the performance of the proposed methods, for different sample sizes, genotype missing rates, degrees of imprinting effects and population models. Simulation results show that the proposed methods control the size well under the null hypothesis of no parent-of-origin effects and Q-PPAT(c) are robust to population stratification. In addition, the power comparison demonstrates that Q-PPAT(c) and Q-MCPPAT(c) for pedigree data are much more powerful than Q-PAT(c) only using two-generation nuclear families selected from extended pedigrees.

Indexed as

Models, GeneticPedigreeAlgorithmsComputer SimulationFemaleGenetic MarkersHumansMaleMonte Carlo MethodQuantitative Trait LociGenetic Markers

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.