Analyzing the Mutant Fitness Distribution

During the screening, a large amount of fitness data is generated, but only the fitness information of the improved mutants is used to continue to the next round of evolution. The large ensemble of less fit mutants provides a view of the local fitness landscape. By analyzing these data, certain statistical landscape parameters can be 

Mean-field theory can be used to predict the effects of mutation rate, landscape ruggedness, and parental fitness on the moments of the mutant fitness distribution1791. In this analysis, only the portion of the mutant distribution that is not dead (zero fitness) or parent (unmutated) is considered. The mutant effects are averaged over the transition probabilities. In order to obtain the fitness distribution, two sets of probabilities are required (1) the probabilities P (o) that a particular amino acid identity o exists at a residue i, and (2) the transition probabilities that one amino acid 

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