title: X-APL: an improved family-based test of association in the presence of linkage for the X chromosome.
abstract: Family-based association methods have been developed primarily for autosomal markers. The X-linked sibling transmission/disequilibrium test (XS-TDT) and the reconstruction-combined TDT for X-chromosome markers (XRC-TDT) are the first association-based methods for testing markers on the X chromosome in family data sets. These are valid tests of association in family triads or discordant sib pairs but are not theoretically valid in multiplex families when linkage is present. Recently, XPDT and XMCPDT, modified versions of the pedigree disequilibrium test (PDT), were proposed. Like the PDT, XPDT compares genotype transmissions from parents to affected offspring or genotypes of discordant siblings; however, the XPDT can have low power if there are many missing parental genotypes. XMCPDT uses a Monte Carlo sampling approach to infer missing parental genotypes on the basis of true or estimated population allele frequencies. Although the XMCPDT was shown to be more powerful than the XPDT, variability in the statistic due to the use of an estimate of allele frequency is not properly accounted for. Here, we present a novel family-based test of association, X-APL, a modification of the test for association in the presence of linkage (APL) test. Like the APL, X-APL can use singleton or multiplex families and properly infers missing parental genotypes in linkage regions by considering identity-by-descent parameters for affected siblings. Sampling variability of parameter estimates is accounted for through a bootstrap procedure. X-APL can test individual marker loci or X-chromosome haplotypes. To allow for different penetrances in males and females, separate sex-specific tests are provided. Using simulated data, we demonstrated validity and showed that the X-APL is more powerful than alternative tests. To show its utility and to discuss interpretation in real-data analysis, we also applied the X-APL to candidate-gene data in a sample of families with Parkinson disease.
authors.affiliation: Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA.
authors.forename: Ren-Hua
authors.initials: RH
authors.lastname: Chung
authors.forename: Richard W
authors.initials: RW
authors.lastname: Morris
authors.forename: Li
authors.initials: L
authors.lastname: Zhang
authors.forename: Yi-Ju
authors.initials: YJ
authors.lastname: Li
authors.forename: Eden R
authors.initials: ER
authors.lastname: Martin
mesh_terms: D041321:Chromosomes, Human, X / Q000235:genetics*; D005190:Family; D005260:Female; D040181:Genetic Diseases, X-Linked / Q000235:genetics*; D005819:Genetic Markers; D006801:Humans; D015810:Linkage Disequilibrium; D008297:Male; D008995:Monoamine Oxidase / Q000235:genetics; D010300:Parkinson Disease / Q000235:genetics; D010375:Pedigree; D035781:Siblings
chemical_list: D005819:Genetic Markers; D008995:Monoamine Oxidase