Hi,
As you didn't include a reproducible example in your question, it is a bit hard to understand what you mean. By "only the numeric data are used to process", you mean a numeric matrix, right?
As far as I understood your question, you have a numeric matrix, but you can't find which genes correspond to which rows in the matrix, probably because you had to remove a column containing gene names. If that is your case, you can assign gene names to the row.names element of your matrix, so you can still see which genes correspond to which rows.
For example, suppose you have a data frame with gene names in the first column and expression values for each sample in all other columns. To create a numeric matrix with gene names in row.names, you would do:
# Simulate a data frame with gene names in the first column, and samples in subsequent columns
exp_df <- data.frame(Gene = paste0("Gene", 1:5), S1 = rnorm(5), S2 = rnorm(5), S3 = rnorm(5))
# Create a numeric matrix from the data frame by removing the first column
exp_matrix <- as.matrix(exp_df[, -1])
# Add genes names (first column of `exp_df` as row names of `exp_matrix`)
rownames(exp_matrix) <- exp_df$Gene
Does that answer your question?
Best,
Fabricio
Good answer, Fabricio, Thank you very much!