DOI: 10.1101/478321Nov 25, 2018Paper

Powerful statistical method to detect disease associated genes using publicly available GWAS summary data

BioRxiv : the Preprint Server for Biology
Jianjun ZhangXuan Guo

Abstract

Genome-wide association studies (GWAS) have thus far achieved substantial success. In the last decade a large number of common variants underlying complex diseases have been identified through GWAS. In most existing GWAS, the identified common variants are obtained by single marker based tests, that is, testing one single nucleotide polymorphisms (SNP) at a time. Generally the basic functional unit of inheritance is a gene, rather than a SNP. Thus, results from gene level association test can be more readily integrated with downstream functional and pathogenic investigation. In this paper, we propose a general gene-based p-value adaptive combination approach (GPA) which can integrate association evidence of multiple genetic variants using only GWAS summary statistics (either p-value or other test statistics). The proposed method could be used to test both continuous and binary traits through not only a single but also multiple studies, which helps overcome the limitation of existing methods that only can be applied to specific type of data. We conducted thorough simulation studies to verify that the proposed method controls type I errors well, and performs favorably compared to single-marker analysis and other existing methods....Continue Reading

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