--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Fri Oct 06 16:46:10 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_2/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_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_2/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_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -4400.59 -4478.35 2 -4408.29 -4474.69 -------------------------------------- TOTAL -4401.29 -4477.69 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_2/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_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 16.597211 2.478963 13.281510 19.474140 16.584730 356.34 387.59 1.001 r(A<->C){all} 0.026546 0.000053 0.013402 0.040819 0.025981 648.22 748.63 1.000 r(A<->G){all} 0.239647 0.001070 0.171298 0.299298 0.240774 159.86 192.33 1.002 r(A<->T){all} 0.031999 0.000072 0.016073 0.048187 0.031269 546.37 578.66 1.005 r(C<->G){all} 0.009031 0.000020 0.001253 0.017680 0.008285 540.18 665.27 1.000 r(C<->T){all} 0.674728 0.001412 0.605575 0.751826 0.673377 155.40 180.76 1.003 r(G<->T){all} 0.018049 0.000042 0.006223 0.030744 0.017317 559.50 626.88 1.000 pi(A){all} 0.289597 0.000177 0.264320 0.316037 0.289718 685.54 801.18 1.000 pi(C){all} 0.210774 0.000124 0.189478 0.232885 0.209951 773.15 867.98 1.000 pi(G){all} 0.298133 0.000181 0.272789 0.325806 0.298033 783.76 866.62 1.000 pi(T){all} 0.201496 0.000120 0.180706 0.223696 0.201413 793.24 847.52 1.000 alpha{1,2} 0.068706 0.000008 0.063635 0.074519 0.068549 534.84 592.78 1.000 alpha{3} 0.258719 0.000183 0.233074 0.284629 0.257990 396.63 480.58 1.003 pinvar{all} 0.381221 0.001193 0.307439 0.441371 0.382288 695.59 785.96 1.001 ------------------------------------------------------------------------------------------------------ * 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 -3654.418098 Model 2: PositiveSelection -3654.418098 Model 0: one-ratio -3661.213426 Model 3: discrete -3647.050595 Model 7: beta -3647.77356 Model 8: beta&w>1 -3647.775811 Model 0 vs 1 13.590655999999399 Model 2 vs 1 0.0 Model 8 vs 7 0.004501999999774853