--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Fri Nov 18 20:00:08 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-PB/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/274/Hsc70-3-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/274/Hsc70-3-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/274/Hsc70-3-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -5363.02 -5379.98 2 -5363.32 -5381.60 -------------------------------------- TOTAL -5363.16 -5381.09 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/274/Hsc70-3-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/274/Hsc70-3-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/274/Hsc70-3-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} 0.675610 0.002300 0.588041 0.772063 0.674169 1188.12 1309.60 1.000 r(A<->C){all} 0.051511 0.000132 0.031488 0.075555 0.050726 1111.65 1194.82 1.001 r(A<->G){all} 0.175306 0.000604 0.129043 0.224259 0.174393 908.78 921.47 1.000 r(A<->T){all} 0.054235 0.000269 0.022471 0.085161 0.052798 1038.10 1052.41 1.001 r(C<->G){all} 0.056266 0.000075 0.040454 0.072783 0.056108 778.46 985.37 1.000 r(C<->T){all} 0.604897 0.000976 0.543389 0.663628 0.605416 814.31 885.24 1.000 r(G<->T){all} 0.057785 0.000130 0.037463 0.081331 0.057229 1026.33 1125.62 1.000 pi(A){all} 0.227010 0.000093 0.208202 0.245889 0.226955 917.83 983.65 1.000 pi(C){all} 0.292458 0.000095 0.272211 0.310319 0.292671 921.38 1117.92 1.000 pi(G){all} 0.292329 0.000102 0.273448 0.311890 0.292104 1237.59 1254.68 1.000 pi(T){all} 0.188203 0.000066 0.174143 0.205252 0.188233 1105.02 1205.77 1.000 alpha{1,2} 0.033334 0.000410 0.000103 0.066781 0.032021 1219.51 1289.50 1.001 alpha{3} 4.103937 0.988982 2.389336 6.087128 4.008867 1350.04 1425.52 1.000 pinvar{all} 0.510990 0.000675 0.457398 0.559969 0.510859 1393.39 1425.73 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