--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Fri Nov 25 15:04:20 WET 2016 codeml.models=0 1 2 3 7 8 mrbayes.mpich= mrbayes.ngen=1000000 tcoffee.alignMethod=CLUSTALW2 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/ADOPS/1/14-3-3zeta-PJ/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/1/14-3-3zeta-PJ/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PJ/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/ADOPS/1/14-3-3zeta-PJ/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -1342.81 -1383.83 2 -1341.12 -1382.53 -------------------------------------- TOTAL -1341.65 -1383.38 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/1/14-3-3zeta-PJ/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PJ/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/ADOPS/1/14-3-3zeta-PJ/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 0.476780 0.063051 0.152655 1.002599 0.408395 720.93 859.17 1.000 r(A<->C){all} 0.070402 0.001539 0.005375 0.145904 0.063982 441.79 479.66 1.000 r(A<->G){all} 0.236200 0.015525 0.037854 0.485439 0.211056 134.28 197.18 1.000 r(A<->T){all} 0.065136 0.001435 0.006683 0.142577 0.058541 428.13 482.49 1.004 r(C<->G){all} 0.045393 0.000819 0.002140 0.100972 0.039549 616.43 616.72 1.000 r(C<->T){all} 0.565716 0.020514 0.303397 0.848663 0.571163 162.65 183.51 1.000 r(G<->T){all} 0.017153 0.000301 0.000014 0.051937 0.011922 558.49 699.48 1.000 pi(A){all} 0.279983 0.000249 0.249437 0.310811 0.279229 992.66 1047.16 1.000 pi(C){all} 0.259685 0.000257 0.228701 0.290107 0.259279 1075.92 1150.07 1.000 pi(G){all} 0.259899 0.000250 0.229396 0.290424 0.259771 1074.32 1149.41 1.001 pi(T){all} 0.200434 0.000203 0.170247 0.226428 0.200408 880.29 1089.11 1.000 alpha{1,2} 0.094111 0.000797 0.036327 0.156475 0.091984 906.89 1098.06 1.000 alpha{3} 1.193212 0.384872 0.249971 2.419900 1.052090 867.19 955.70 1.000 pinvar{all} 0.826546 0.001175 0.758937 0.885881 0.830428 813.30 903.53 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 -1263.066771 Model 2: PositiveSelection -1263.066771 Model 0: one-ratio -1264.026193 Model 3: discrete -1263.063085 Model 7: beta -1263.3924 Model 8: beta&w>1 -1263.066768 Model 0 vs 1 1.9188439999998081 Model 2 vs 1 0.0 Model 8 vs 7 0.6512640000000829