--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Fri Nov 25 00:59:00 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/30/CadN-PC/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/30/CadN-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/30/CadN-PC/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/30/CadN-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -31171.24 -31188.70 2 -31171.74 -31186.66 -------------------------------------- TOTAL -31171.46 -31188.13 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/30/CadN-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/30/CadN-PC/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/30/CadN-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 1.189595 0.000931 1.133053 1.252446 1.188950 1410.92 1455.96 1.000 r(A<->C){all} 0.082354 0.000029 0.072153 0.093428 0.082244 978.32 1108.31 1.001 r(A<->G){all} 0.295840 0.000109 0.273485 0.315164 0.295598 702.09 756.34 1.002 r(A<->T){all} 0.069888 0.000030 0.060169 0.081398 0.069806 1047.05 1063.25 1.001 r(C<->G){all} 0.056879 0.000018 0.048792 0.065396 0.056788 869.67 989.98 1.000 r(C<->T){all} 0.440788 0.000125 0.418677 0.462162 0.440747 559.01 661.98 1.002 r(G<->T){all} 0.054252 0.000020 0.045356 0.063237 0.054095 901.03 1023.86 1.000 pi(A){all} 0.253458 0.000019 0.244998 0.262244 0.253323 697.27 840.55 1.000 pi(C){all} 0.261944 0.000018 0.253629 0.269772 0.261936 661.84 706.34 1.000 pi(G){all} 0.266981 0.000019 0.258335 0.275215 0.266916 497.45 797.75 1.000 pi(T){all} 0.217617 0.000015 0.209741 0.225156 0.217544 632.87 809.01 1.001 alpha{1,2} 0.085978 0.000009 0.080313 0.091878 0.085898 1439.94 1470.47 1.000 alpha{3} 8.213413 1.628749 5.921812 10.713210 8.106510 1296.62 1311.23 1.000 pinvar{all} 0.438154 0.000120 0.416767 0.459369 0.438205 1486.78 1493.89 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 -28979.626918 Model 2: PositiveSelection -28979.626938 Model 0: one-ratio -29045.783047 Model 3: discrete -28949.183788 Model 7: beta -28959.628256 Model 8: beta&w>1 -28957.150338 Model 0 vs 1 132.3122579999981 Model 2 vs 1 3.9999998989515007E-5 Model 8 vs 7 4.955836000001