--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Mon Oct 31 19:37:21 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/128/CG34135-PC/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/128/CG34135-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/128/CG34135-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/128/CG34135-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -1397.97 -1416.91 2 -1397.73 -1415.30 -------------------------------------- TOTAL -1397.84 -1416.40 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/128/CG34135-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/128/CG34135-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/128/CG34135-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} 1.576089 0.040436 1.181268 1.948034 1.559422 1152.11 1276.67 1.000 r(A<->C){all} 0.098913 0.001038 0.039216 0.162479 0.096602 737.94 823.77 1.000 r(A<->G){all} 0.221962 0.002158 0.133351 0.314957 0.219489 574.55 667.95 1.000 r(A<->T){all} 0.171376 0.002830 0.068286 0.269458 0.169705 554.55 569.91 1.000 r(C<->G){all} 0.051327 0.000308 0.020564 0.087596 0.049935 876.27 1066.24 1.000 r(C<->T){all} 0.360973 0.002830 0.260173 0.464100 0.360128 679.42 752.86 1.000 r(G<->T){all} 0.095450 0.000855 0.038454 0.152650 0.092364 910.66 971.12 1.000 pi(A){all} 0.173138 0.000282 0.141803 0.206391 0.172728 1294.15 1305.32 1.001 pi(C){all} 0.314535 0.000428 0.273723 0.354166 0.314167 1154.10 1223.84 1.000 pi(G){all} 0.278350 0.000424 0.240417 0.321302 0.277967 1193.27 1334.14 1.000 pi(T){all} 0.233977 0.000363 0.197657 0.272579 0.233701 1007.43 1022.75 1.000 alpha{1,2} 0.074869 0.000116 0.054041 0.095729 0.074391 1404.65 1452.82 1.000 alpha{3} 2.588000 0.626118 1.257271 4.189710 2.460149 1184.46 1280.65 1.000 pinvar{all} 0.384506 0.002871 0.281405 0.488287 0.385063 1309.37 1376.30 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 -1271.471055 Model 2: PositiveSelection -1271.469716 Model 0: one-ratio -1271.53949 Model 3: discrete -1271.469716 Model 7: beta -1271.469025 Model 8: beta&w>1 -1271.470364 Model 0 vs 1 0.13686999999981708 Model 2 vs 1 0.0026779999998325366 Model 8 vs 7 0.0026779999998325366