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Name	C-GWAS
Type	Health and Disease Detection
Developers	Ziyi Xiong, Fan Liu, Xingjian Gao
Description	C-GWAS is a powerful method for combining GWAS summary statistics of multiple potentially related traits and detect SNPs with multi-trait effects.C-GWAS begins with GWASs summary as inputs and outputs a single vector of combined p-values testing if the null is deviated. For each SNP, the null is the absence of any effect on all traits, and the alternative is that its effect deviates from 0 for at least one trait. C-GWAS integrates two different statistical methods with complementary statistical features to ensure the optimal power under various and complex scenarios while keeping a stable study-wide type-I error rate. The first method is called iterative effect based inverse covariance weighting (i-EbICoW) and the second method is called truncated Wald test (TWT).C-GWAS controls the study-wide type-I error rate in an empirical manner via simulations and adjust the resultant p-values in such a way that they are directly comparable with those from traditional GWAS of a single trait.
Downlaod	https://ngdc.cncb.ac.cn/biocode/tools/7350
Article	https://www.nature.com/articles/s41467-022-35328-9

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