run.meta

#!/usr/bin/env Rscript
library(GMMAT)
library(data.table)
## Expects : a variant set file and a set of directories
argv = commandArgs(trailingOnly = TRUE)
group_file=argv[1]
argv=argv[-1]

cohorts=NULL
files=NULL
for(d in argv){
  flist=list.files(d, pattern="*.out$")
  cohort=strsplit(flist[1], ".", fixed=T)[[1]][1]
  cohorts=c(cohorts,cohort)
  filepat=sub(paste0(cohort,"."), "", flist)
  cat(paste("[INFO]", length(flist), "files detected for cohort", cohort, "\n"))
  if(is.null(files)){
    files=filepat
    cat(paste("[INFO] init with",length(files), "\n"))
  }else{
    oldfiles=files
    files=intersect(filepat, files)
    if(length(oldfiles)!=length(files)){
      print(paste("[Warning]: Dropped", length(oldfiles)-length(files), "files not found in this cohort"))
    }
  }
}


#we now meta-analyse every file separately
cat(paste("[INFO] Meta-analysing",length(files), "files for",length(cohorts),"cohorts.\n"))
flush.console()
for(f in files){
  toanalyse=paste(argv, paste(cohorts,f,sep="."), sep="/")
  nfiles=sapply(toanalyse, function(x){
      scorefiles=Sys.glob(paste0(x, ".score.*"))
      return(length(scorefiles))
  })
meta=SMMAT.meta(meta.files.prefix=toanalyse, n.files=nfiles,
        group.file=group_file,
        MAF.range=c(1e-10, 0.05),
        MAF.weights.beta = c(1,1),
        miss.cutoff=0.01,
        tests=c("O", "E"),
        rho=(0:10)/10,
        use.minor.allele=T
          )
print(paste(paste(cohorts, collapse="."), f, sep="."))
fwrite(meta, paste(paste(cohorts, collapse="."), f, sep="."), sep="\t", na=NA, quote=F)

}