--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Wed May 09 12:45:09 WEST 2018 codeml.models=0 1 2 3 7 8 mrbayes.mpich= mrbayes.ngen=1000000 tcoffee.alignMethod=MUSCLE tcoffee.params= tcoffee.maxSeqs=0 codeml.bin=codeml mrbayes.tburnin=2500 codeml.dir= input.sequences= mrbayes.pburnin=2500 mrbayes.bin=mb_adops tcoffee.bin=t_coffee_ADOPS mrbayes.dir=/usr/bin/ tcoffee.dir= tcoffee.minScore=3 input.fasta=/opt/ADOPS1/DNG_N2/NS2A_4/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS1/DNG_N2/NS2A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/NS2A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run2.p": (Use the harmonic mean for Bayes factor comparisons of models) (Values are saved to the file /opt/ADOPS1/DNG_N2/NS2A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -6452.27 -6498.03 2 -6452.42 -6496.20 -------------------------------------- TOTAL -6452.34 -6497.49 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS1/DNG_N2/NS2A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/NS2A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run2.p": Summaries are based on a total of 3002 samples from 2 runs. Each run produced 2001 samples of which 1501 samples were included. Parameter summaries saved to file "/opt/ADOPS1/DNG_N2/NS2A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 9.336506 0.452743 8.038047 10.687740 9.301376 464.62 602.83 1.000 r(A<->C){all} 0.047047 0.000085 0.029947 0.065949 0.046691 679.13 740.11 1.000 r(A<->G){all} 0.214645 0.000326 0.178394 0.247501 0.214197 503.95 553.81 1.002 r(A<->T){all} 0.057231 0.000076 0.041865 0.075537 0.056888 791.97 899.13 1.000 r(C<->G){all} 0.051669 0.000109 0.031085 0.070905 0.051188 654.72 739.61 1.000 r(C<->T){all} 0.603610 0.000499 0.562566 0.647572 0.602958 369.49 481.63 1.002 r(G<->T){all} 0.025798 0.000068 0.009991 0.041353 0.025378 753.67 796.04 1.000 pi(A){all} 0.306025 0.000126 0.284311 0.327768 0.305865 594.29 684.45 1.000 pi(C){all} 0.215488 0.000092 0.197316 0.234215 0.215474 719.79 744.39 1.000 pi(G){all} 0.241226 0.000110 0.220255 0.260976 0.241085 860.57 921.65 1.000 pi(T){all} 0.237261 0.000098 0.217759 0.256455 0.236936 771.12 852.37 1.000 alpha{1,2} 0.390034 0.001514 0.320042 0.466318 0.387319 712.54 958.34 1.000 alpha{3} 4.174785 0.951195 2.517902 6.140725 4.048279 1040.30 1142.35 1.000 pinvar{all} 0.026314 0.000314 0.000006 0.060721 0.023523 1233.55 1312.99 1.000 ------------------------------------------------------------------------------------------------------ * Convergence diagnostic (ESS = Estimated Sample Size); min and avg values correspond to minimal and average ESS among runs. ESS value below 100 may indicate that the parameter is undersampled. + Convergence diagnostic (PSRF = Potential Scale Reduction Factor; Gelman and Rubin, 1992) should approach 1.0 as runs converge. Setting sumt conformat to Simple --- CODEML SUMMARY Model 1: NearlyNeutral -6133.329351 Model 2: PositiveSelection -6133.329351 Model 0: one-ratio -6149.747654 Model 3: discrete -6082.695715 Model 7: beta -6083.05543 Model 8: beta&w>1 -6083.055832 Model 0 vs 1 32.83660599999894 Model 2 vs 1 0.0 Model 8 vs 7 8.039999993343372E-4