--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Fri Nov 18 20:29:02 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/274/Hsc70-3-PC/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/274/Hsc70-3-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/274/Hsc70-3-PC/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/274/Hsc70-3-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -5363.20 -5379.40 2 -5363.08 -5383.35 -------------------------------------- TOTAL -5363.14 -5382.68 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/274/Hsc70-3-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/274/Hsc70-3-PC/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/274/Hsc70-3-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 0.676422 0.002202 0.587626 0.768165 0.674507 1354.94 1371.63 1.000 r(A<->C){all} 0.051050 0.000129 0.030719 0.073907 0.050361 834.53 964.47 1.000 r(A<->G){all} 0.175997 0.000597 0.130049 0.225277 0.175568 756.28 919.88 1.000 r(A<->T){all} 0.054288 0.000278 0.021413 0.085922 0.052965 897.15 1019.01 1.001 r(C<->G){all} 0.056226 0.000077 0.039697 0.073440 0.055778 1081.91 1195.00 1.000 r(C<->T){all} 0.604434 0.000981 0.540164 0.661228 0.604250 776.05 874.70 1.000 r(G<->T){all} 0.058004 0.000130 0.035226 0.079707 0.057265 1188.55 1207.46 1.000 pi(A){all} 0.226782 0.000090 0.209088 0.246017 0.226620 835.02 941.83 1.000 pi(C){all} 0.292682 0.000091 0.274187 0.310665 0.292539 1229.50 1248.25 1.001 pi(G){all} 0.292272 0.000099 0.272858 0.311793 0.292265 920.62 1030.85 1.000 pi(T){all} 0.188264 0.000069 0.171652 0.203455 0.188174 888.46 940.97 1.000 alpha{1,2} 0.033267 0.000411 0.000184 0.067247 0.031786 855.54 874.36 1.000 alpha{3} 4.123766 0.991690 2.425675 6.119612 4.017863 1337.91 1363.59 1.000 pinvar{all} 0.511172 0.000695 0.459691 0.563002 0.511903 1247.68 1374.34 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 -4932.66204 Model 2: PositiveSelection -4932.859411 Model 0: one-ratio -4932.85941 Model 3: discrete -4932.136197 Model 7: beta -4932.138108 Model 8: beta&w>1 -4932.140858 Model 0 vs 1 0.39473999999972875 Model 2 vs 1 0.3947420000004058 Model 8 vs 7 0.005499999999301508