--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Sun Oct 08 03:47:30 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_5/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_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B3_A/Zika-NS4B_5/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_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -3609.72 -3705.56 2 -3613.01 -3706.65 -------------------------------------- TOTAL -3610.38 -3706.25 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/DATA/Zika/B3_A/Zika-NS4B_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B3_A/Zika-NS4B_5/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_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 15.264623 2.282281 12.350370 18.298370 15.248630 528.91 572.09 1.000 r(A<->C){all} 0.023677 0.000056 0.010464 0.038767 0.022949 644.03 740.61 1.001 r(A<->G){all} 0.242827 0.001936 0.148156 0.325439 0.244216 193.16 221.31 1.000 r(A<->T){all} 0.059445 0.000162 0.035405 0.083768 0.058813 476.21 477.24 1.000 r(C<->G){all} 0.012366 0.000032 0.003160 0.024003 0.011492 381.21 483.88 1.000 r(C<->T){all} 0.632217 0.002760 0.534817 0.742530 0.629648 183.95 215.00 1.000 r(G<->T){all} 0.029469 0.000083 0.013396 0.048432 0.028410 501.36 526.26 1.000 pi(A){all} 0.263622 0.000224 0.233116 0.291366 0.263681 732.51 849.29 1.000 pi(C){all} 0.250307 0.000186 0.224573 0.276967 0.250425 918.74 921.18 1.000 pi(G){all} 0.259313 0.000215 0.231060 0.287604 0.259242 650.75 796.15 1.000 pi(T){all} 0.226758 0.000181 0.199632 0.251982 0.226721 832.25 840.18 1.000 alpha{1,2} 0.076450 0.000012 0.069776 0.083272 0.076277 829.98 847.73 1.000 alpha{3} 0.305445 0.000587 0.263908 0.354637 0.302732 565.99 601.20 1.000 pinvar{all} 0.292154 0.001639 0.211599 0.366891 0.293969 667.64 709.60 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 -3235.201478 Model 2: PositiveSelection -3235.176513 Model 0: one-ratio -3277.003946 Model 3: discrete -3234.226796 Model 7: beta -3235.963243 Model 8: beta&w>1 -3235.963784 Model 0 vs 1 83.60493599999973 Model 2 vs 1 0.04993000000013126 Model 8 vs 7 0.001081999999769323