--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Thu Jul 12 02:13:48 WEST 2018 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= input.sequences= mrbayes.pburnin=2500 mrbayes.bin=mb_adops tcoffee.bin=t_coffee_ADOPS mrbayes.dir=/usr/bin/ tcoffee.dir= tcoffee.minScore=3 input.fasta=/opt/ADOPS1/DNG_N3/NS4B_1/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS1/DNG_N3/NS4B_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/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/ADOPS1/DNG_N3/NS4B_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -5962.81 -6007.61 2 -5961.47 -6005.50 -------------------------------------- TOTAL -5961.93 -6007.03 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS1/DNG_N3/NS4B_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/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/ADOPS1/DNG_N3/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} 7.289096 0.234855 6.392444 8.228090 7.277219 887.52 908.19 1.000 r(A<->C){all} 0.044034 0.000059 0.029100 0.059385 0.043968 923.45 991.33 1.000 r(A<->G){all} 0.231089 0.000413 0.193975 0.272343 0.230222 523.92 537.84 1.001 r(A<->T){all} 0.057129 0.000080 0.040361 0.074667 0.056645 843.52 888.62 1.004 r(C<->G){all} 0.028866 0.000066 0.013203 0.044447 0.028441 673.83 773.88 1.000 r(C<->T){all} 0.614799 0.000607 0.567814 0.662558 0.615368 516.69 525.79 1.003 r(G<->T){all} 0.024084 0.000062 0.009297 0.039176 0.023592 785.81 806.63 1.001 pi(A){all} 0.337796 0.000148 0.315387 0.362197 0.337679 943.87 985.45 1.001 pi(C){all} 0.232480 0.000107 0.212495 0.252871 0.232382 802.77 911.41 1.001 pi(G){all} 0.217346 0.000113 0.195555 0.237754 0.217197 800.54 888.79 1.000 pi(T){all} 0.212378 0.000093 0.192874 0.230510 0.212287 835.04 898.33 1.001 alpha{1,2} 0.179789 0.000165 0.155748 0.204818 0.179078 902.08 1042.60 1.000 alpha{3} 4.313709 0.748055 2.719269 5.994901 4.203316 1416.71 1458.85 1.001 pinvar{all} 0.131891 0.000769 0.080795 0.186981 0.131564 1235.35 1243.18 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 -5408.319805 Model 2: PositiveSelection -5408.319805 Model 0: one-ratio -5421.441971 Model 3: discrete -5346.019052 Model 7: beta -5347.505404 Model 8: beta&w>1 -5347.507834 Model 0 vs 1 26.244332000000213 Model 2 vs 1 0.0 Model 8 vs 7 0.004859999999098363