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Rare variant association analysis in case-parents studies by allowing for missing parental genotypes

BACKGROUND: The development of next-generation sequencing technologies has facilitated the identification of rare variants. Family-based design is commonly used to effectively control for population admixture and substructure, which is more prominent for rare variants. Case-parents studies, as typic...

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Detalles Bibliográficos
Autores principales: Li, Yumei, Xiang, Yang, Xu, Chao, Shen, Hui, Deng, Hongwen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5769338/
https://www.ncbi.nlm.nih.gov/pubmed/29334894
http://dx.doi.org/10.1186/s12863-018-0597-8
Descripción
Sumario:BACKGROUND: The development of next-generation sequencing technologies has facilitated the identification of rare variants. Family-based design is commonly used to effectively control for population admixture and substructure, which is more prominent for rare variants. Case-parents studies, as typical strategies in family-based design, are widely used in rare variant-disease association analysis. Current methods in case-parents studies are based on complete case-parents data; however, parental genotypes may be missing in case-parents trios, and removing these data may lead to a loss in statistical power. The present study focuses on testing for rare variant-disease association in case-parents study by allowing for missing parental genotypes. RESULTS: In this report, we extended the collapsing method for rare variant association analysis in case-parents studies to allow for missing parental genotypes, and investigated the performance of two methods by using the difference of genotypes between affected offspring and their corresponding “complements” in case-parent trios and TDT framework. Using simulations, we showed that, compared with the methods just only using complete case-parents data, the proposed strategy allowing for missing parental genotypes, or even adding unrelated affected individuals, can greatly improve the statistical power and meanwhile is not affected by population stratification. CONCLUSIONS: We conclude that adding case-parents data with missing parental genotypes to complete case-parents data set can greatly improve the power of our strategy for rare variant-disease association. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12863-018-0597-8) contains supplementary material, which is available to authorized users.