Skewed-LRT scores are computed across cell lines, so they describe whether a gene has a long tail. This is to say, that metric characterizes the distribution of gene effects, which sounds to me, different than identifying hits.
If you are interested in calling a “hit” in a cell line as which lines are dependent, it may make sense to look at the “dependency probability” dataset and call those lines where the probably is > 0.5 as hits.
(see also: What thresholds should I use to decide if a gene is really having a significant effect on a cell line? )
