--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Sat Nov 12 09:13:54 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/2/ab-PF/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/2/ab-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/2/ab-PF/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/2/ab-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -9550.27 -9564.63 2 -9550.33 -9564.45 -------------------------------------- TOTAL -9550.30 -9564.54 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/2/ab-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/2/ab-PF/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/2/ab-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 1.133528 0.003943 1.007033 1.253249 1.130120 1036.72 1268.86 1.000 r(A<->C){all} 0.075632 0.000092 0.055634 0.093940 0.075321 891.53 954.66 1.002 r(A<->G){all} 0.180961 0.000282 0.148015 0.212395 0.180614 706.56 715.16 1.001 r(A<->T){all} 0.134029 0.000322 0.101443 0.168899 0.133404 1041.34 1061.22 1.001 r(C<->G){all} 0.043106 0.000031 0.032758 0.054420 0.042920 1074.55 1192.05 1.000 r(C<->T){all} 0.523047 0.000623 0.472464 0.569185 0.522883 683.67 763.48 1.000 r(G<->T){all} 0.043225 0.000088 0.025319 0.061649 0.042579 975.43 1048.50 1.000 pi(A){all} 0.229296 0.000056 0.215766 0.244921 0.229113 990.22 1013.60 1.001 pi(C){all} 0.340521 0.000067 0.325138 0.357279 0.340520 787.90 877.71 1.000 pi(G){all} 0.288791 0.000062 0.274011 0.304492 0.288829 879.53 1100.25 1.000 pi(T){all} 0.141392 0.000033 0.130235 0.152459 0.141373 971.13 1073.46 1.003 alpha{1,2} 0.142276 0.000113 0.122072 0.163455 0.141735 1484.13 1489.55 1.000 alpha{3} 3.176430 0.490580 1.982382 4.609904 3.081406 1363.07 1411.36 1.001 pinvar{all} 0.339863 0.000788 0.282087 0.391741 0.340916 1305.30 1388.63 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 -8333.050317 Model 2: PositiveSelection -8333.050317 Model 0: one-ratio -8403.270713 Model 3: discrete -8304.51193 Model 7: beta -8304.768658 Model 8: beta&w>1 -8304.770348 Model 0 vs 1 140.44079200000124 Model 2 vs 1 0.0 Model 8 vs 7 0.0033799999982875306