--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Sat Dec 10 18:28:29 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/443/zip-PF/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/443/zip-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/443/zip-PF/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/443/zip-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -19574.27 -19591.15 2 -19574.24 -19591.97 -------------------------------------- TOTAL -19574.25 -19591.64 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/443/zip-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/443/zip-PF/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/443/zip-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 1.207474 0.001629 1.130149 1.284942 1.207563 1282.00 1389.40 1.000 r(A<->C){all} 0.058845 0.000029 0.049164 0.069884 0.058675 930.83 971.52 1.001 r(A<->G){all} 0.284328 0.000164 0.259685 0.308688 0.284274 878.45 886.20 1.001 r(A<->T){all} 0.096858 0.000091 0.077889 0.115338 0.096620 662.30 754.85 1.000 r(C<->G){all} 0.026906 0.000009 0.021147 0.032790 0.026848 948.09 1059.66 1.000 r(C<->T){all} 0.484903 0.000233 0.456949 0.515437 0.484711 696.38 720.38 1.001 r(G<->T){all} 0.048160 0.000030 0.037384 0.058937 0.048042 1154.53 1168.39 1.000 pi(A){all} 0.266930 0.000030 0.256979 0.278684 0.266975 1008.68 1017.82 1.000 pi(C){all} 0.261743 0.000028 0.251442 0.272177 0.261865 957.70 1071.02 1.000 pi(G){all} 0.304539 0.000031 0.293654 0.315212 0.304363 977.51 1017.67 1.000 pi(T){all} 0.166788 0.000020 0.158158 0.175481 0.166801 859.79 985.86 1.000 alpha{1,2} 0.088573 0.000015 0.081574 0.096647 0.088572 910.27 1142.46 1.000 alpha{3} 8.235864 1.799719 5.780923 11.024210 8.132401 1501.00 1501.00 1.000 pinvar{all} 0.396692 0.000208 0.370470 0.426531 0.396466 1391.44 1433.30 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 -17979.696617 Model 2: PositiveSelection -17979.696643 Model 0: one-ratio -18002.62548 Model 3: discrete -17960.642716 Model 7: beta -17967.956561 Model 8: beta&w>1 -17966.815377 Model 0 vs 1 45.85772599999473 Model 2 vs 1 5.199999577598646E-5 Model 8 vs 7 2.282368000000133