--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Wed Nov 16 02:42:26 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/241/endos-PB/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/241/endos-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/241/endos-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/241/endos-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -1034.90 -1053.40 2 -1035.07 -1058.14 -------------------------------------- TOTAL -1034.98 -1057.45 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/241/endos-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/241/endos-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/241/endos-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} 0.863136 0.021989 0.599122 1.171308 0.847059 1227.64 1273.68 1.000 r(A<->C){all} 0.058287 0.000649 0.015551 0.111912 0.054851 539.14 625.23 1.003 r(A<->G){all} 0.159413 0.002739 0.065851 0.261017 0.152574 548.35 590.34 1.000 r(A<->T){all} 0.148576 0.004208 0.029406 0.273836 0.141780 351.68 390.19 1.000 r(C<->G){all} 0.027806 0.000157 0.005802 0.052689 0.026196 885.66 886.53 1.000 r(C<->T){all} 0.563357 0.007302 0.400954 0.724100 0.563382 480.71 486.62 1.000 r(G<->T){all} 0.042561 0.000589 0.004372 0.091429 0.037802 771.67 941.43 1.002 pi(A){all} 0.264085 0.000514 0.221633 0.310340 0.263245 961.17 1032.97 1.000 pi(C){all} 0.320399 0.000584 0.272469 0.368952 0.320476 1075.12 1103.42 1.000 pi(G){all} 0.296258 0.000531 0.249833 0.340095 0.296015 1240.91 1302.34 1.000 pi(T){all} 0.119259 0.000288 0.088493 0.153409 0.118241 922.32 998.44 1.000 alpha{1,2} 0.107837 0.000753 0.061004 0.165277 0.105908 1156.75 1224.56 1.000 alpha{3} 2.155340 0.650239 0.820605 3.719296 2.017830 1007.36 1199.36 1.000 pinvar{all} 0.326241 0.007543 0.147511 0.490026 0.330972 1122.50 1175.32 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 -947.591513 Model 2: PositiveSelection -947.591513 Model 0: one-ratio -954.840262 Model 3: discrete -944.979338 Model 7: beta -945.027418 Model 8: beta&w>1 -945.02786 Model 0 vs 1 14.497498000000178 Model 2 vs 1 0.0 Model 8 vs 7 8.840000000418513E-4