--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Mon Nov 06 17:35:10 WET 2017 codeml.models=0 1 2 3 7 8 mrbayes.mpich= mrbayes.ngen=1000000 tcoffee.alignMethod=MUSCLE 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/ADOPS1/Zikaomegamapresults/E/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS1/Zikaomegamapresults/E/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/Zikaomegamapresults/E/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/ADOPS1/Zikaomegamapresults/E/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -5848.52 -5915.94 2 -5845.71 -5905.07 -------------------------------------- TOTAL -5846.34 -5915.25 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS1/Zikaomegamapresults/E/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/Zikaomegamapresults/E/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/ADOPS1/Zikaomegamapresults/E/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 1.133307 0.005177 0.994493 1.278667 1.132369 861.87 966.70 1.000 r(A<->C){all} 0.030545 0.000044 0.018127 0.043413 0.030059 858.95 871.15 1.000 r(A<->G){all} 0.163993 0.000468 0.120537 0.203859 0.162416 326.95 383.81 1.002 r(A<->T){all} 0.034608 0.000057 0.021110 0.049862 0.034148 668.60 716.70 1.000 r(C<->G){all} 0.021679 0.000031 0.011621 0.032941 0.021169 704.21 821.66 1.000 r(C<->T){all} 0.720793 0.000783 0.665378 0.773396 0.722229 302.12 334.85 1.002 r(G<->T){all} 0.028383 0.000042 0.016420 0.041449 0.028098 745.26 748.22 1.000 pi(A){all} 0.262595 0.000109 0.240664 0.281603 0.262395 812.25 909.88 1.002 pi(C){all} 0.232886 0.000091 0.215850 0.252868 0.232893 944.55 1118.86 1.000 pi(G){all} 0.280738 0.000119 0.258213 0.300637 0.280894 709.23 909.74 1.000 pi(T){all} 0.223781 0.000086 0.206455 0.242775 0.223708 980.33 1018.73 1.000 alpha{1,2} 0.164407 0.000210 0.138357 0.195143 0.163339 1081.91 1176.46 1.000 alpha{3} 3.755622 0.926429 2.123162 5.680947 3.645178 1427.04 1464.02 1.002 pinvar{all} 0.247361 0.001527 0.172606 0.324963 0.247737 866.32 993.96 1.002 ------------------------------------------------------------------------------------------------------ * 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 -5514.964793 Model 2: PositiveSelection -5515.564412 Model 0: one-ratio -5515.564658 Model 3: discrete -5509.224666 Model 7: beta -5509.941309 Model 8: beta&w>1 -5509.946172 Model 0 vs 1 1.1997300000002724 Model 2 vs 1 1.1992379999992409 Model 8 vs 7 0.009726000000227941