I think "the best" way to do this is going to depend on what your question is, unfortunately.
For example, let's say you're trying to find which genes vary by tumour stage.
Variance of a given gene might be high across all samples, in which case it has no relation to the stage and might be useless for you.
Alternatively, you may have a lowly-to-moderately expressed gene that does not vary much between samples of the same stage, but differs between stages, which is useful for you.
However, because it's not highly-expressed, its variance may be small compared to the variance of highly-expressed genes and skipped over.
But if you're trying to do sequencing batch correction to identify batch effects, looking at raw sequencing counts and doing some type of quantile normalization might be all you need.
So I don't think there's a one-size-fits-all answer to your question, unless you're able to refine it a little bit