tidyImportedDataUnderscore <- function(data) {

  # note: I tested this against my original script and it gives identical results
  # pair == TRUE means that the headers of the columns have some information about what pair the larvae were from
  # if there is no pair data, set pair = FALSE so we don't screw up the columns when we split

  rawdata2 <- t(data)

  rawNames <- rownames(rawdata2)
  rawNames[1] <- "FishName"
  rownames(rawdata2) <- rawNames

  rawdata4 <- as.data.frame(rawdata2)
  rawdata4 <- rownames_to_column(rawdata4)

  columnHeaders <- rawdata4[1,]

  colnames(rawdata4) <- columnHeaders
  rawdata4 <- rawdata4[-1,] #gets rid of header row

  rawdata4 <- as_tibble(rawdata4)

  splitCols <- rawdata4 %>%
    separate("FishName", into = c("fishNum","allElse"), sep = "_") %>%
    separate("allElse", into = c("pair", "geno", "pheno", "collected", "imaged"), sep = "\\.") %>%
    unite("uniqueID", fishNum:imaged, remove = FALSE) %>%
    mutate(imaged = as.character(imaged)) %>%
    mutate(collected = as.character(collected)) %>%
    clean_names()

  return(splitCols)
}