--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Fri Nov 25 22:04:22 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/1/5PtaseI-PF/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/1/5PtaseI-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/5PtaseI-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/1/5PtaseI-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -8847.52 -8865.80 2 -8847.63 -8862.42 -------------------------------------- TOTAL -8847.57 -8865.14 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/1/5PtaseI-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/5PtaseI-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/1/5PtaseI-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} 0.887435 0.002468 0.793564 0.988190 0.886320 1399.09 1450.04 1.000 r(A<->C){all} 0.096964 0.000108 0.076210 0.115626 0.096577 1020.64 1117.10 1.000 r(A<->G){all} 0.257464 0.000376 0.216434 0.294368 0.257452 750.30 890.44 1.000 r(A<->T){all} 0.101488 0.000135 0.080163 0.125651 0.101215 1097.89 1117.57 1.000 r(C<->G){all} 0.091401 0.000109 0.070795 0.111304 0.091060 841.44 1018.91 1.001 r(C<->T){all} 0.385959 0.000487 0.341569 0.427906 0.385526 807.66 876.09 1.000 r(G<->T){all} 0.066724 0.000101 0.048357 0.086950 0.066391 988.92 1124.70 1.000 pi(A){all} 0.280879 0.000072 0.264816 0.297789 0.280890 1125.97 1143.40 1.000 pi(C){all} 0.257914 0.000070 0.241128 0.273970 0.257947 1152.15 1161.35 1.000 pi(G){all} 0.235088 0.000064 0.219931 0.250891 0.234953 754.16 1028.41 1.000 pi(T){all} 0.226119 0.000064 0.210238 0.241625 0.226067 933.41 1063.33 1.000 alpha{1,2} 0.230197 0.000527 0.185426 0.273018 0.228179 1132.01 1275.39 1.000 alpha{3} 3.178917 0.635412 1.795807 4.728869 3.067282 972.67 1148.74 1.000 pinvar{all} 0.374775 0.001089 0.310911 0.440002 0.376342 1137.29 1167.15 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 -8203.203783 Model 2: PositiveSelection -8203.203783 Model 0: one-ratio -8285.96666 Model 3: discrete -8186.471264 Model 7: beta -8186.591177 Model 8: beta&w>1 -8186.591304 Model 0 vs 1 165.52575399999841 Model 2 vs 1 0.0 Model 8 vs 7 2.539999986765906E-4