transfExprFormat <- function(exprMatrix = normCount, colData = colData) {
df <- as.data.frame(exprMatrix)
colData$mainCode <- colnames(df)[-which(colnames(df) == "GeneSymbol")]
print(colnames(df))
long_df <- tidyr::pivot_longer(df, cols = -GeneSymbol, names_to = "sample", values_to = "expression")
long_df$group <- colData$subCode[match(long_df$sample, colData$mainCode)]
return(long_df)
}
If colData looks like this:
> +-------+--------+-------+ │
│ | _c0|mainCode|subCode| │
│ +-------+--------+-------+ │
│ |DDBM322| DDBM322| case| │
│ |DDBM319| DDBM319|control| │
│ |DDBM316| DDBM316|control| │
│ |DDBM317| DDBM317|control| │
│ |DDBM321| DDBM321| case| │
│ |DDBM325| DDBM325| case| │
│ +-------+--------+-------+ │
Then sequence information will lose after applying colData$mainCode <- colnames(df)[-which(colnames(df) == "GeneSymbol")]
If colData looks like this:
Then sequence information will lose after applying
colData$mainCode <- colnames(df)[-which(colnames(df) == "GeneSymbol")]