--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Wed Dec 20 05:36:06 WET 2017 codeml.models= 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/DGA_B3/NS5_5/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/DGA_B3/NS5_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_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/DGA_B3/NS5_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -23288.12 -23323.87 2 -23288.87 -23329.17 -------------------------------------- TOTAL -23288.42 -23328.48 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/DGA_B3/NS5_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_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/DGA_B3/NS5_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} 8.061799 0.129426 7.374975 8.768002 8.044148 406.71 489.73 1.000 r(A<->C){all} 0.035072 0.000010 0.028731 0.041246 0.035008 378.86 605.98 1.000 r(A<->G){all} 0.194707 0.000095 0.175852 0.213502 0.194346 364.83 369.54 1.000 r(A<->T){all} 0.043532 0.000015 0.035703 0.050999 0.043615 832.63 858.04 1.000 r(C<->G){all} 0.022492 0.000011 0.016124 0.028837 0.022345 807.43 841.25 1.002 r(C<->T){all} 0.680304 0.000147 0.657529 0.704235 0.680692 277.45 310.09 1.000 r(G<->T){all} 0.023893 0.000016 0.016436 0.031805 0.023793 569.19 675.45 1.001 pi(A){all} 0.365063 0.000042 0.351920 0.376659 0.365069 532.43 650.61 1.000 pi(C){all} 0.224436 0.000028 0.214117 0.234494 0.224285 590.99 613.37 1.000 pi(G){all} 0.231947 0.000033 0.220742 0.242907 0.232079 578.71 691.51 1.000 pi(T){all} 0.178554 0.000024 0.169176 0.188422 0.178432 396.28 464.12 1.000 alpha{1,2} 0.189319 0.000053 0.175460 0.203537 0.189102 1264.18 1306.72 1.000 alpha{3} 6.620637 0.912778 4.852459 8.529687 6.546054 1382.33 1441.67 1.000 pinvar{all} 0.138172 0.000205 0.109989 0.166131 0.138298 938.31 1027.36 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: One dN/dS ratio for branches, -22524.808358