--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Sat Jul 14 02:32:04 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_4/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS1/DNG_N3/NS4B_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/NS4B_4/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_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -6409.09 -6458.67 2 -6410.03 -6451.32 -------------------------------------- TOTAL -6409.45 -6457.98 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS1/DNG_N3/NS4B_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/NS4B_4/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_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 7.909196 0.270976 6.959896 8.964944 7.888652 675.83 829.13 1.000 r(A<->C){all} 0.036271 0.000042 0.024257 0.049454 0.035922 766.98 906.55 1.000 r(A<->G){all} 0.194807 0.000304 0.161512 0.230717 0.194421 671.71 682.69 1.000 r(A<->T){all} 0.050833 0.000055 0.037212 0.065883 0.050450 678.28 710.60 1.000 r(C<->G){all} 0.019573 0.000043 0.007049 0.032079 0.018900 841.11 926.17 1.000 r(C<->T){all} 0.663741 0.000480 0.622244 0.707063 0.663914 553.08 650.94 1.000 r(G<->T){all} 0.034776 0.000064 0.019976 0.050886 0.034309 709.74 754.67 1.000 pi(A){all} 0.334330 0.000157 0.311186 0.359637 0.334279 773.28 813.87 1.000 pi(C){all} 0.238828 0.000117 0.219027 0.261326 0.238623 744.87 834.79 1.000 pi(G){all} 0.215352 0.000116 0.193782 0.236033 0.215248 877.48 879.94 1.000 pi(T){all} 0.211491 0.000093 0.193446 0.230742 0.211482 584.31 729.94 1.000 alpha{1,2} 0.183191 0.000130 0.162631 0.206899 0.182649 1170.96 1235.41 1.000 alpha{3} 4.157995 0.585639 2.799276 5.754164 4.085948 1380.22 1385.46 1.001 pinvar{all} 0.131907 0.000848 0.076748 0.190035 0.131558 995.81 1104.42 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 -5898.529147 Model 2: PositiveSelection -5898.529147 Model 0: one-ratio -5942.816926 Model 3: discrete -5838.7087 Model 7: beta -5842.545025 Model 8: beta&w>1 -5840.12694 Model 0 vs 1 88.57555800000046 Model 2 vs 1 0.0 Model 8 vs 7 4.836170000000493