--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Thu Oct 05 23:37:12 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/B3_A/Zika-NS4B_1/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/DATA/Zika/B3_A/Zika-NS4B_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B3_A/Zika-NS4B_1/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/B3_A/Zika-NS4B_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -3415.01 -3502.53 2 -3408.77 -3509.13 -------------------------------------- TOTAL -3409.46 -3508.44 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/DATA/Zika/B3_A/Zika-NS4B_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B3_A/Zika-NS4B_1/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/B3_A/Zika-NS4B_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 15.101058 1.771210 12.543350 17.713610 15.053870 365.53 665.69 1.001 r(A<->C){all} 0.019764 0.000052 0.006825 0.033594 0.018879 252.24 295.90 1.000 r(A<->G){all} 0.182177 0.002173 0.108438 0.281746 0.172486 109.30 117.77 1.004 r(A<->T){all} 0.039531 0.000115 0.021553 0.061335 0.038335 231.55 337.67 1.003 r(C<->G){all} 0.003496 0.000009 0.000001 0.009521 0.002692 459.03 495.23 1.007 r(C<->T){all} 0.734913 0.003181 0.617848 0.828604 0.743729 103.77 114.71 1.006 r(G<->T){all} 0.020120 0.000052 0.006988 0.034403 0.019212 206.78 376.46 1.013 pi(A){all} 0.261451 0.000225 0.233679 0.291664 0.261674 838.56 933.51 1.000 pi(C){all} 0.252563 0.000199 0.223881 0.279417 0.252300 946.30 965.98 1.000 pi(G){all} 0.260868 0.000224 0.231771 0.290070 0.260537 828.43 859.92 1.000 pi(T){all} 0.225118 0.000177 0.199206 0.250935 0.224682 560.44 667.67 1.000 alpha{1,2} 0.073438 0.000010 0.067709 0.079962 0.073309 403.54 435.66 1.001 alpha{3} 0.282344 0.000418 0.243481 0.322988 0.280347 346.93 555.10 1.003 pinvar{all} 0.262039 0.001768 0.177148 0.341720 0.261534 443.51 503.98 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 -2917.05587 Model 2: PositiveSelection -2917.05587 Model 0: one-ratio -2947.643808 Model 3: discrete -2915.834153 Model 7: beta -2917.867125 Model 8: beta&w>1 -2917.867171 Model 0 vs 1 61.175875999999334 Model 2 vs 1 0.0 Model 8 vs 7 9.199999931297498E-5