Select top 100 genes ranked by variance in read counts
I assume by "reverse sort of variance" you mean "highest variance". Assuming you made a matrix out of that (set the row names to the first column and then remove it) and called it m:

sel = order(apply(m, 1, var), decreasing=TRUE)[1:100]


sel then contains the indices into your matrix (or the original dataframe).

BTW, I hope you're not filtering by variance before performing differential expression. That would be incredibly incorrect. Doing this sort of filtering for performing PCA or something like that can be useful, though you should really be using normalized counts (or a transformation of them).