@article {45,
	title = {FARVATX: Family-Based Rare Variant Association Test for X-Linked Genes.},
	journal = {Genet Epidemiol},
	volume = {40},
	year = {2016},
	month = {2016 Sep},
	pages = {475-85},
	abstract = {<p>Although the X chromosome has many genes that are functionally related to human diseases, the complicated biological properties of the X chromosome have prevented efficient genetic association analyses, and only a few significantly associated X-linked variants have been reported for complex traits. For instance, dosage compensation of X-linked genes is often achieved via the inactivation of one allele in each X-linked variant in females; however, some X-linked variants can escape this X chromosome inactivation. Efficient genetic analyses cannot be conducted without prior knowledge about the gene expression process of X-linked variants, and misspecified information can lead to power loss. In this report, we propose new statistical methods for rare X-linked variant genetic association analysis of dichotomous phenotypes with family-based samples. The proposed methods are computationally efficient and can complete X-linked analyses within a few hours. Simulation studies demonstrate the statistical efficiency of the proposed methods, which were then applied to rare-variant association analysis of the X chromosome in chronic obstructive pulmonary disease. Some promising significant X-linked genes were identified, illustrating the practical importance of the proposed methods.</p>},
	keywords = {Alleles, Chromosomes, Human, X, Female, Genes, X-Linked, Genetic Variation, Humans, Models, Genetic, Pedigree, Phenotype, X Chromosome Inactivation},
	issn = {1098-2272},
	doi = {10.1002/gepi.21979},
	author = {Choi, Sungkyoung and Lee, Sungyoung and Qiao, Dandi and Hardin, Megan and Cho, Michael H and Silverman, Edwin K and Park, Taesung and Won, Sungho}
}
