--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Thu Feb 18 16:59:54 WET 2016 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/B4_A/Zika-NS5_4/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/DATA/Zika/B4_A/Zika-NS5_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B4_A/Zika-NS5_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/B4_A/Zika-NS5_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -9092.17 -9173.46 2 -9087.97 -9190.61 -------------------------------------- TOTAL -9088.65 -9189.91 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/DATA/Zika/B4_A/Zika-NS5_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B4_A/Zika-NS5_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/B4_A/Zika-NS5_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} 1.082852 0.003223 0.973582 1.197589 1.080876 459.88 477.61 1.000 r(A<->C){all} 0.022532 0.000018 0.014307 0.031134 0.022322 814.98 908.29 1.000 r(A<->G){all} 0.219084 0.000443 0.179541 0.259466 0.217997 413.71 444.60 1.000 r(A<->T){all} 0.027275 0.000030 0.017051 0.037932 0.026899 733.37 739.62 1.002 r(C<->G){all} 0.006560 0.000006 0.002064 0.011187 0.006269 682.25 705.63 1.000 r(C<->T){all} 0.704344 0.000579 0.660163 0.752669 0.705359 329.62 370.40 1.000 r(G<->T){all} 0.020206 0.000020 0.011900 0.029312 0.019950 543.81 643.98 1.001 pi(A){all} 0.279823 0.000063 0.264921 0.295600 0.279672 844.22 898.85 1.000 pi(C){all} 0.227426 0.000052 0.213801 0.241997 0.227649 654.10 709.96 1.000 pi(G){all} 0.295871 0.000066 0.280237 0.311779 0.295871 886.94 890.36 1.003 pi(T){all} 0.196880 0.000046 0.183018 0.210027 0.196781 807.42 888.73 1.000 alpha{1,2} 0.109801 0.000078 0.093189 0.127740 0.109636 1111.52 1175.65 1.001 alpha{3} 4.898783 1.062486 3.077460 6.942204 4.789856 1116.79 1204.92 1.000 pinvar{all} 0.266643 0.000915 0.206271 0.325327 0.267805 927.39 985.31 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 -8491.066751 Model 2: PositiveSelection -8491.066747 Model 0: one-ratio -8538.702434 Model 3: discrete -8487.233605 Model 7: beta -8487.588366 Model 8: beta&w>1 -8487.590316 Model 0 vs 1 95.27136600000085 Model 2 vs 1 7.99999907030724E-6 Model 8 vs 7 0.003899999999703141