--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Wed Nov 02 14:53:29 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/14/Arl5-PA/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/14/Arl5-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/14/Arl5-PA/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/14/Arl5-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -1790.96 -1809.44 2 -1790.54 -1807.98 -------------------------------------- TOTAL -1790.73 -1808.95 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/14/Arl5-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/14/Arl5-PA/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/14/Arl5-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 1.360324 0.022172 1.097790 1.672114 1.353018 1202.77 1276.11 1.000 r(A<->C){all} 0.099697 0.000529 0.057888 0.145736 0.097994 801.80 909.01 1.000 r(A<->G){all} 0.220806 0.001570 0.147453 0.300013 0.217351 743.81 774.80 1.001 r(A<->T){all} 0.017110 0.000296 0.000013 0.051406 0.011960 522.26 757.58 1.000 r(C<->G){all} 0.055933 0.000190 0.030834 0.084527 0.054713 1046.00 1050.16 1.000 r(C<->T){all} 0.572883 0.002536 0.472851 0.666363 0.573493 650.77 746.29 1.001 r(G<->T){all} 0.033571 0.000206 0.007509 0.061226 0.032221 995.13 1033.17 1.000 pi(A){all} 0.232541 0.000313 0.199698 0.268381 0.232665 933.09 993.88 1.000 pi(C){all} 0.286523 0.000303 0.250996 0.318808 0.286229 1212.98 1296.45 1.000 pi(G){all} 0.299230 0.000334 0.264494 0.336610 0.298622 1122.53 1160.52 1.000 pi(T){all} 0.181706 0.000218 0.153801 0.210788 0.181481 970.80 1099.16 1.000 alpha{1,2} 0.072469 0.000241 0.045571 0.104129 0.073167 958.46 1019.05 1.001 alpha{3} 3.430087 0.932108 1.761111 5.327696 3.287892 1203.73 1302.82 1.000 pinvar{all} 0.303055 0.002824 0.195675 0.400741 0.303969 1166.90 1331.58 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 -1592.168673 Model 2: PositiveSelection -1592.166905 Model 0: one-ratio -1592.281347 Model 3: discrete -1592.166905 Model 7: beta -1592.165772 Model 8: beta&w>1 -1592.200271 Model 0 vs 1 0.22534800000039468 Model 2 vs 1 0.003535999999712658 Model 8 vs 7 0.06899799999973766