read_write_GRM_gz

X = GXM
filename = paste0(data.dir,"tempo/gcta-run/gxm.grm")
ids = rnadata$sidno
write_GRMgz = function(X,filename,ids)
{
 #X[upper.tri(X,diag=TRUE)]
 rmat = row(X)
 cmat = col(X)
 omat = cbind(cmat[upper.tri(cmat,diag=TRUE)],rmat[upper.tri(rmat,diag=TRUE)],ncol(rnamat),X[upper.tri(X,diag=TRUE)])
 write_tsv(data.frame(omat),path=filename,col_names = FALSE)
 if(length(list.files(paste0(filename,".gz") ) )>0) system(paste0("rm ",filename,".gz"))
 system(paste0("gzip ",filename))
 write_tsv(data.frame(ids,ids),path=paste0(filename,".id"),col_names = FALSE)
}
write_GRMgz(GXM,filename,ids)


## function in OmicKriging modified from original fro GCTA documentation
read_GRMBin <- 
function (prefix, size = 4) 
{
    sum_i <- function(i) {
        return(sum(1:i))
    }
    BinFileName <- paste(prefix, ".bin", sep = "")
    NFileName <- paste(prefix, ".N.bin", sep = "")
    IDFileName <- paste(prefix, ".id", sep = "")
    id <- read.table(IDFileName)
    n <- dim(id)[1]
    BinFile <- file(BinFileName, "rb")
    grm <- readBin(BinFile, n = n * (n + 1)/2, what = numeric(0), 
        size = size)
    NFile <- file(NFileName, "rb")
    N <- readBin(NFile, n = 1, what = numeric(0), size = size)
    i <- sapply(1:n, sum_i)
    close(BinFile)
    close(NFile)
    diag.elem <- grm[i]
    off.diag.elem <- grm[-i]
    X <- diag(diag.elem)
    X[upper.tri(X, diag = FALSE)] <- off.diag.elem
    X <- X + t(X) - diag(diag(X))
    rownames(X) <- id$V2
    colnames(X) <- id$V2
    return(X)
}

Another version of readGRMbin is here with slightly different output format https://ibg.colorado.edu/cdrom2022/day7/Answers/RR_WorkshopDay7.html

## this may be faster when the sample size is large. It uses the exact formula for sum_i rather than calculate with a for loop. But it didn't make a lot of difference when n~3100
read_GRMBin_opt <- 
function (prefix, size = 4) 
{
    #sum_i <- function(i) {
    #    return(sum(1:i))
    #}
    BinFileName <- paste(prefix, ".bin", sep = "")
    NFileName <- paste(prefix, ".N.bin", sep = "")
    IDFileName <- paste(prefix, ".id", sep = "")
    id <- read.table(IDFileName)
    n <- dim(id)[1]
    BinFile <- file(BinFileName, "rb")
    grm <- readBin(BinFile, n = n * (n + 1)/2, what = numeric(0), 
        size = size)
    NFile <- file(NFileName, "rb")
    N <- readBin(NFile, n = 1, what = numeric(0), size = size)
    #i <- sapply(1:n, sum_i)
    nvec <- 1:n
    i <- nvec * (nvec + 1)/2
    close(BinFile)
    close(NFile)
    diag.elem <- grm[i]
    off.diag.elem <- grm[-i]
    X <- diag(diag.elem)
    X[upper.tri(X, diag = FALSE)] <- off.diag.elem
    X <- X + t(X) - diag(diag(X))
    rownames(X) <- id$V2
    colnames(X) <- id$V2
    return(X)
}