--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Sun Oct 08 06:02:51 WEST 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=/usr/bin/ input.sequences= mrbayes.pburnin=2500 mrbayes.bin=mb tcoffee.bin=t_coffee mrbayes.dir=/usr/bin/ tcoffee.dir= tcoffee.minScore=3 input.fasta=/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_4/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_4/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/DATA/Zika/B2_A/Zika-NS1_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -4251.85 -4338.35 2 -4251.76 -4335.80 -------------------------------------- TOTAL -4251.80 -4337.73 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_4/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/DATA/Zika/B2_A/Zika-NS1_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 16.204429 2.763839 12.793460 19.258120 16.249460 177.22 180.94 1.022 r(A<->C){all} 0.031193 0.000076 0.016078 0.049308 0.030296 198.60 214.43 1.005 r(A<->G){all} 0.210437 0.002583 0.096297 0.294179 0.218719 57.20 68.60 1.046 r(A<->T){all} 0.031975 0.000089 0.015497 0.051734 0.031330 148.51 179.81 1.012 r(C<->G){all} 0.007503 0.000017 0.000916 0.015475 0.006895 660.84 722.23 1.000 r(C<->T){all} 0.694252 0.003821 0.593376 0.836197 0.682576 51.17 63.36 1.048 r(G<->T){all} 0.024640 0.000061 0.009547 0.039124 0.023998 238.79 248.35 1.011 pi(A){all} 0.286575 0.000185 0.259524 0.311500 0.286354 675.91 795.45 1.005 pi(C){all} 0.210384 0.000121 0.189323 0.231898 0.209933 740.98 798.58 1.002 pi(G){all} 0.298313 0.000178 0.271243 0.323495 0.297991 547.88 694.98 1.000 pi(T){all} 0.204727 0.000118 0.182902 0.225058 0.204593 942.11 961.54 1.000 alpha{1,2} 0.069273 0.000011 0.063215 0.075482 0.069039 146.69 177.51 1.018 alpha{3} 0.252505 0.000182 0.226996 0.279545 0.251704 351.32 429.96 1.000 pinvar{all} 0.409235 0.001561 0.328038 0.483098 0.411992 114.94 133.66 1.020 ------------------------------------------------------------------------------------------------------ * 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 -3497.189929 Model 2: PositiveSelection -3497.190052 Model 0: one-ratio -3501.803461 Model 3: discrete -3489.842715 Model 7: beta -3490.529667 Model 8: beta&w>1 -3490.530396 Model 0 vs 1 9.2270639999997 Model 2 vs 1 2.459999996062834E-4 Model 8 vs 7 0.0014580000006390037