This is an earlier version of the Gumbel method that identifies essential genes based on how unlikely ‘gaps’ (or consecutive runs of TA sites with 0 insertions) are, given the overall level of saturation. It is a frequentist (non-Bayesian) model that uses the Gumbel Extreme-Value Distribution as a likelihood function. This is the analysis used in our paper on cholesterol catabolism (Griffin et al., 2011). All things considered, you are probably better off using the hierarchical-Bayesian Gumbel model above, which does a better job of estimating internal parameters.