--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Fri Nov 25 13:23:56 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-PB/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/1/14-3-3zeta-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PB/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-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -1544.28 -1567.13 2 -1544.31 -1565.61 -------------------------------------- TOTAL -1544.29 -1566.64 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/1/14-3-3zeta-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PB/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-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 0.245856 0.001604 0.174180 0.325750 0.241814 1136.30 1318.65 1.000 r(A<->C){all} 0.113183 0.001243 0.049168 0.182604 0.109564 846.81 852.88 1.000 r(A<->G){all} 0.153348 0.001798 0.079640 0.240865 0.148999 811.48 856.54 1.000 r(A<->T){all} 0.066514 0.001006 0.012708 0.130478 0.062035 755.27 884.75 1.000 r(C<->G){all} 0.063165 0.000684 0.017561 0.114195 0.060155 884.58 960.25 1.001 r(C<->T){all} 0.553864 0.005036 0.409065 0.684867 0.555828 666.32 723.35 1.000 r(G<->T){all} 0.049926 0.000809 0.004077 0.103858 0.045310 858.11 927.24 1.000 pi(A){all} 0.285634 0.000263 0.254883 0.317959 0.285132 1182.12 1247.07 1.000 pi(C){all} 0.260975 0.000235 0.233004 0.293073 0.260752 1171.72 1183.73 1.000 pi(G){all} 0.258169 0.000240 0.227530 0.288645 0.258184 1228.06 1273.73 1.000 pi(T){all} 0.195222 0.000197 0.168133 0.222360 0.195008 961.99 1200.21 1.000 alpha{1,2} 0.056728 0.001797 0.000108 0.133540 0.048256 1004.00 1252.50 1.000 alpha{3} 2.093251 0.661590 0.714309 3.649766 1.970407 1230.32 1365.66 1.000 pinvar{all} 0.476075 0.008265 0.291909 0.633806 0.486202 1308.58 1341.06 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 -1451.36118 Model 2: PositiveSelection -1451.36118 Model 0: one-ratio -1458.92382 Model 3: discrete -1451.332921 Model 7: beta -1451.333746 Model 8: beta&w>1 -1451.361179 Model 0 vs 1 15.125279999999748 Model 2 vs 1 0.0 Model 8 vs 7 0.054865999999947235