hakyim

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)

hakyim

## Relatively fast linear regression

fastlm = function(xx,yy)
{
  ## compute betahat (regression coef) and pvalue with Ftest
  ## for now it does not take covariates

  df1 = 2
  df0 = 1
  ind = !is.na(xx) & !is.na(yy)

hakyim

# calculate ptrs function
calc_ptrs <- function(expr, weights)
{
  fast_generate_trait(expr, weights) %>% as.data.frame() %>% rownames_to_column(var = "IID") %>% tibble()
}

fast_generate_trait <- function(expr, weights){
  # convert the predicted df into a matrix
  if(!is.matrix(expr)) test <- expr %>% column_to_rownames(var = "IID") %>%
    as.matrix() else test <- expr