title: A powerful association test for qualitative traits incorporating imprinting effects using general pedigree data.
abstract: For qualitative traits and diallelic marker loci, the pedigree disequilibrium test (PDT) based on general pedigrees and its extension (Monte Carlo PDT (MCPDT)) for dealing with missing genotypes are simple and powerful tests for association. There is an increasing interest of incorporating imprinting into association analysis. However, PDT and MCPDT do not take account of the information on imprinting effects in the analysis, which may reduce their test powers when the effects are present. On the other hand, the transmission disequilibrium test with imprinting (TDTI*) combines imprinting into the mapping of association variants. However, TDTI* only accommodates two-generation nuclear families and thus is not suitable for extended pedigrees. In this article, we first extend PDT to incorporate imprinting and propose PDTI for complete pedigrees (no missing genotypes). To fully utilize pedigrees with missing genotypes, we further develop the Monte Carlo PDTI (MCPDTI) statistic based on Monte Carlo sampling and estimation. Both PDTI and MCPDTI are derived in a two-stage framework. Simulation study shows that PDTI and MCPDTI control the size well under the null hypothesis of no association and are more powerful than PDT and TDTI* (based on a sample of nuclear families randomly selecting from pedigrees) when imprinting effects exist.
authors.affiliation: State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou, China.
authors.forename: Ji-Yuan
authors.initials: JY
authors.lastname: Zhou
authors.affiliation: State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou, China.
authors.forename: Hai-Qiang
authors.initials: HQ
authors.lastname: He
authors.affiliation: State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou, China.
authors.forename: Xiao-Ping
authors.initials: XP
authors.lastname: You
authors.affiliation: State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou, China.
authors.forename: Shao-Zhan
authors.initials: SZ
authors.lastname: Li
authors.affiliation: State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou, China.
authors.forename: Ping-Yan
authors.initials: PY
authors.lastname: Chen
authors.affiliation: Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong, China.
authors.forename: Wing Kam
authors.initials: WK
authors.lastname: Fung
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D005260:Female; D018392:Genomic Imprinting / Q000235:genetics*; D005838:Genotype; D006239:Haplotypes; D006801:Humans; D015810:Linkage Disequilibrium; D008297:Male; D008957:Models, Genetic; D009010:Monte Carlo Method; D009679:Nuclear Family; D010375:Pedigree; D010641:Phenotype