# Save symmetic matrix to GCTA GRM format. GRM (Genetic Relatedness Matrix) is the core formt of GCTA, this function saves a R symmetric matrix to a file set recgnizable by GCTA. ```r saveGRM(pfx, grm, vcm = NULL, fid = NULL) ``` ## Arguments - `pfx`: prefix of data files - `grm`: genome relatedness matrix to save - `vcm`: variant counts matrix to save (def=1). - `fid`: separator after family ID. (def=NULL) ## Details Three files will be saved: - **.grm.bin :**: genetic relatedness matrix in binary - **.grm.id :**: FID and IID for N individuals in text - **.grm.N.bin :**: variant count matrix (VCM) in binary FID and IID will be generated if the `grm` to be saved has no row names. When save the `vcm`, if a single number is given, this number is used as the variant count for all entries in the GRM. `saveGRM` is useful in exporting customized kinship matrices (such as a Gaussian or a Laplacian kernel) to a GRM acceptable by GCTA, which are not supported by GCTA's own GRM builder. ## Examples ```r pfx <- file.path(system.file("extdata", package="plinkFile"), "m20") gmx <- readBED(pfx) # read genotype matrix from PLINK BED. gmx <- scale(gmx) # standardize tmp <- tempdir() # for example outputs dir.create(tmp, FALSE) # kinship matrix as Gaussian kernel, built from the first 10 variants gmx.gau <- gmx[, +(1:10)] # the first 10 variants not.na.gau <- tcrossprod(!is.na(gmx.gau)) # variant count matrix kin.gau <- exp(as.matrix(-dist(gmx.gau, "euc")) / not.na.gau) print(kin.gau) # the Gaussian kernel out.gau <- file.path(tmp, "m20.gau") saveGRM(out.gau, kin.gau, not.na.gau) # gau.grm.* should appear # kinship matrix as Laplacian kernel, built without the first 10 variants gmx.lap <- gmx[, -(1:10)] # drop the first 10 variants not.na.lap <- tcrossprod(!is.na(gmx.lap)) # variant count matrix kin.lap <- exp(as.matrix(-dist(gmx.lap, "man")) / not.na.lap) out.lap <- file.path(tmp, "m20.lap") print(kin.lap) # the Laplacian kernel saveGRM(out.lap, kin.lap, not.na.lap) # lap.grm.* should appear # merge kinship in R language for a radius based function kernel matrix not.na.rbf <- not.na.gau + not.na.lap kin.rbf <- (kin.gau * not.na.gau + kin.lap * not.na.lap) / not.na.rbf print(kin.rbf) out.rbf <- file.path(tmp, "m20.rbf") saveGRM(out.rbf, kin.rbf, not.na.rbf) # rbf.grm.* should appear # show saved matrices, then clean up dir(tmp, "(gau|lap|rbf)") unlink(tmp, recursive=TRUE) ```

saveGRM function