Fisher's exact test on values from large dataframe and bypassing errors

Question

I have a dataframe which is 214 columns long and many rows long, and I want to perform a fisher\'s exact test for each row using values from 4 columns.

An example s

Answer 1

You can include an if-else statement in your loop like this:

res <- NULL
for (i in 1:nrow(df)){
  table <- matrix(c(df[i,4], df[i,5], df[i,2], df[i,3]), ncol = 2, byrow = TRUE)
# if any NA occurs in your table save an error in p else run the fisher test
  if(any(is.na(table))) p <- "error" else p <- fisher.test(table, alternative="greater")$p.value
  # save all p values in a vector
  res <- c(res,p)
}
df$fishers <- res

Or put the code in a function and use apply instead of a loop:

foo <- function(y){
  # include here as.numeric to be sure that your values are numeric:
  table <-  matrix(as.numeric(c(y[4], y[5], y[2], y[3])), ncol = 2, byrow = TRUE)
  if(any(is.na(table))) p <- "error" else p <- fisher.test(table, alternative="greater")$p.value
  p
} 
df$fishers <- apply(df, 1, foo)