MultiMeta: Meta-analysis for multivariate genome-wide association scan

In MultiABEL: Multi-Trait Genome-Wide Association Analysis

Description

The function performs meta-analysis for multiple multivariate GWA analyses

Usage

MultiMeta(reslist, outfile = "Multivariate_meta-analysis_results.txt")

Arguments

reslist	A list where each element is a multivariate GWA result of class "MultiRes".
outfile	A string giving the path and file name of the output file. By default, a file named 'Multivariate_meta-analysis_results.txt' will be written into the current working directory.

Value

The function returns a matrix containing the meta-analysis results, where the row names are the variants names, and the column names are the names of the studies provided in reslist or generated by the program if no names are given, with an extra column "p.meta" containing the meta-analysis P-values. The results are also written into outfile.

Author(s)

Xia Shen

References

Xia Shen, ..., Gordan Lauc, Jim Wilson, Yurii Aulchenko (2014). Multi-omic-variate analysis identified the association between 14q32.33 and compound N-Glycosylation of human Immunoglobulin G Submitted.

See Also

Multivariate

Examples

## Not run: 
## loading two gwaa.data sets in GenABEL
data(ge03d2)
data(ge03d2ex)

## in each dataset, running multivariate GWAS for 3 traits: height, weight, bmi
res1 <- Multivariate(gwaa.data = ge03d2, trait.cols = c(5, 6, 8), 
                     covariate.cols = c(2, 3))
res2 <- Multivariate(gwaa.data = ge03d2ex.clean, trait.cols = c(5, 6, 8), 
                     covariate.cols = c(2, 3))

## running meta-analysis by combining the P-values
meta <- MultiMeta(list(res1, res2))

## End(Not run)

MultiABEL documentation built on May 2, 2019, 5:57 p.m.