Meta-analysis of multivariate GWAS results

Description

multi_meta returns the meta-analysis results for multivariate GWAS across different cohorts.

Usage

  multi_meta(files = c(), N = c(),
    output.file = "Meta_Results.txt", size.chunks = 5e+06,
    min.pop = 2, sep = "\t")

Arguments

Details

This function applies an inverse-variance based method to meta-analyse multivariate GWAS results. In particular, given n different cohorts, for which p phenotypes have been tested for genome-wide association, the results for each cohort will have p different effect size coefficients i.e. beta values (one per each phenotype) and a variance/covariance pxp matrix representing beta's variances and covariances. In particular, the function is built to consider the output from the GEMMA software multivariate association testing. If your output is not produced with GEMMA, the function works on any results file containing the following column names:

• chr Chromosome

• ps Position

• rs SNP name

• allele1 Effect allele

• allele0 Non-effect allele

• af Effect-allele frequency

• beta_1, beta_2, ..., beta_p Effect sizes for each of the p traits

• Vbeta_1_1, Vbeta_1_2, ..., Vbeta_1_p, Vbeta_2_2, ..., Vbeta_2_p, ..., Vbeta_p_p variance-covariance matrix entries (diagonal and upper triangle values only, since this matrix is symmetric)

The function divides input files into chunks based on position. Only one chunk at a time is read and analysed; thus a limited amount of data is loaded in the workspace at one given time. Default chunk dimension is 5 Mb for which low memory is required (<250 MB for 2 cohorts). If you have larger RAM availability, sparse markers or a limited number of cohorts, change chunks' dimension from the command line.

Examples

file1=system.file("extdata", "Example_file_1.txt", package="MultiMeta")
file2=system.file("extdata", "Example_file_2.txt", package="MultiMeta")
multi_meta(files=c(file1,file2), N=c(1200,600), sep=" ",
output.file="Output_from_running_example.txt")

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(MultiMeta)
Loading required package: gtable
Loading required package: grid
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/MultiMeta/multi_meta.Rd_%03d_medium.png", width=480, height=480)
> ### Name: multi_meta
> ### Title: Meta-analysis of multivariate GWAS results
> ### Aliases: multi_meta
> 
> ### ** Examples
> 
> file1=system.file("extdata", "Example_file_1.txt", package="MultiMeta")
> file2=system.file("extdata", "Example_file_2.txt", package="MultiMeta")
> multi_meta(files=c(file1,file2), N=c(1200,600), sep=" ",
+ output.file="Output_from_running_example.txt")
There were 50 or more warnings (use warnings() to see the first 50)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>