--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Tue Nov 29 16:38:20 WET 2016 codeml.models=0 1 2 3 7 8 mrbayes.mpich= mrbayes.ngen=1000000 tcoffee.alignMethod=CLUSTALW2 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/ADOPS/59/CG13024-PB/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/59/CG13024-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/59/CG13024-PB/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/59/CG13024-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -2426.96 -2443.86 2 -2427.10 -2444.07 -------------------------------------- TOTAL -2427.03 -2443.97 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/59/CG13024-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/59/CG13024-PB/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/59/CG13024-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 1.004648 0.012456 0.806620 1.234269 0.996298 1217.83 1320.82 1.000 r(A<->C){all} 0.089564 0.000428 0.050870 0.129398 0.087875 915.11 998.83 1.000 r(A<->G){all} 0.210864 0.001282 0.141135 0.280922 0.208585 839.39 864.07 1.000 r(A<->T){all} 0.101494 0.000852 0.047083 0.160701 0.099267 1020.98 1057.71 1.000 r(C<->G){all} 0.084672 0.000297 0.051391 0.118019 0.083938 802.53 954.78 1.000 r(C<->T){all} 0.464835 0.002383 0.370195 0.559038 0.465560 624.50 681.68 1.000 r(G<->T){all} 0.048571 0.000370 0.012783 0.085004 0.046742 994.58 1075.27 1.000 pi(A){all} 0.244072 0.000236 0.213065 0.273137 0.243804 681.79 849.37 1.000 pi(C){all} 0.318011 0.000238 0.288030 0.347349 0.317587 1174.18 1208.64 1.000 pi(G){all} 0.262192 0.000232 0.232789 0.291849 0.262020 992.08 1079.31 1.000 pi(T){all} 0.175725 0.000163 0.149717 0.199258 0.175639 1051.85 1153.16 1.000 alpha{1,2} 0.124867 0.000373 0.089709 0.162963 0.123570 1280.41 1339.82 1.003 alpha{3} 2.846692 0.792181 1.321923 4.649449 2.735073 1240.40 1355.95 1.000 pinvar{all} 0.454350 0.002338 0.353485 0.541223 0.456702 1040.04 1199.42 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 -2075.381039 Model 2: PositiveSelection -2075.381039 Model 0: one-ratio -2085.143498 Model 3: discrete -2072.665669 Model 7: beta -2074.670976 Model 8: beta&w>1 -2072.86893 Model 0 vs 1 19.52491800000007 Model 2 vs 1 0.0 Model 8 vs 7 3.604091999999582