期刊
STATISTICAL METHODS IN MEDICAL RESEARCH
卷 26, 期 2, 页码 567-582出版社
SAGE PUBLICATIONS LTD
DOI: 10.1177/0962280214551815
关键词
Chromosome X; combining p values; generalized genetic model; GWAS; single-nucleotide polymorphism; trend test
类别
资金
- School of Public Health, Indiana University Bloomington
- Simons Foundation [280601]
In the past decade, hundreds of genome-wide association studies have been conducted to detect the significant single-nucleotide polymorphisms that are associated with certain diseases. However, most of the data from the X chromosome were not analyzed and only a few significant associated single-nucleotide polymorphisms from the X chromosome have been identified from genome-wide association studies. This is mainly due to the lack of powerful statistical tests. In this paper, we propose a novel statistical approach that combines the information of single-nucleotide polymorphisms on the X chromosome from both males and females in an efficient way. The proposed approach avoids the need of making strong assumptions about the underlying genetic models. Our proposed statistical test is a robust method that only makes the assumption that the risk allele is the same for both females and males if the single-nucleotide polymorphism is associated with the disease for both genders. Through simulation study and a real data application, we show that the proposed procedure is robust and have excellent performance compared to existing methods. We expect that many more associated single-nucleotide polymorphisms on the X chromosome will be identified if the proposed approach is applied to current available genome-wide association studies data.
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