Table 2 

Expected prediction error under various experimental designs

Experimental designType of mutation*Landscapes using this protocolnWmaxσQ
5 mutations, 25 genotypesRA, C0.850.680.640.570.390.370.440.350.320.670.490.43
4 mutations, 24 genotypesR-0.930.80.780.790.580.540.420.360.350.640.520.45
8 mutations, 8 single and 20 double mutantsRS-0.80.580.540.680.480.50.370.30.290.550.440.4
20 mutations, up to 121 genotypesRB0.720.620.540.480.250.210.350.230.220.620.450.39
9 mutations, 9 single mutants, 18 double mutantsISD0.740.680.630.370.220.150.380.270.240.450.370.32
6 mutations, 6 single mutants, 15 double mutantsISE0.810.80.760.450.250.180.390.330.30.670.590.54
5 mutations, 25 genotypesIS, high fitness combinationH1, H20.860.740.610.
4 mutations, 24 genotypesIS, small fitness effect mutantsH30.80.840.780.690.520.430.50.410.380.690.480.36
4 mutations, 24 genotypesIS, large fitness effect mutantsH40.940.720.560.
  • Prediction error for the four parameters of Fisher’s model, for several experimental designs (based on single and double mutants, or complete sets of mutations and all associated genotypes) and selection procedures (* R: random, IS: independently selected, CS: co-selected mutations), when the 6 summary statistics were used in the ABC algorithm. For each parameter, the three lowest prediction errors are in bold, highlighting the protocol and inference algorithms that perform best.