--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Fri Nov 25 13:57:54 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/1/14-3-3zeta-PE/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/1/14-3-3zeta-PE/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PE/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/1/14-3-3zeta-PE/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -1342.72 -1382.31 2 -1342.33 -1381.64 -------------------------------------- TOTAL -1342.51 -1382.03 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/1/14-3-3zeta-PE/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PE/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/1/14-3-3zeta-PE/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 0.473544 0.067333 0.142869 1.018249 0.400158 662.16 821.53 1.001 r(A<->C){all} 0.068818 0.001499 0.007393 0.146321 0.062591 823.08 826.55 1.000 r(A<->G){all} 0.221598 0.013474 0.036367 0.454872 0.201844 188.17 190.86 1.007 r(A<->T){all} 0.068243 0.001607 0.005154 0.148570 0.060632 497.57 514.43 1.000 r(C<->G){all} 0.045412 0.000869 0.000300 0.102767 0.039104 359.43 459.65 1.002 r(C<->T){all} 0.578885 0.020094 0.316472 0.850431 0.581910 188.85 192.58 1.005 r(G<->T){all} 0.017044 0.000298 0.000001 0.051334 0.011402 575.97 635.25 1.000 pi(A){all} 0.279823 0.000253 0.248380 0.309435 0.279650 988.65 1223.69 1.000 pi(C){all} 0.259029 0.000238 0.228630 0.288443 0.258887 926.24 939.33 1.001 pi(G){all} 0.260970 0.000249 0.229218 0.291322 0.260985 911.35 1014.28 1.000 pi(T){all} 0.200178 0.000213 0.171262 0.227612 0.199568 1055.21 1121.96 1.000 alpha{1,2} 0.093441 0.000880 0.036617 0.165185 0.091221 822.79 970.66 1.000 alpha{3} 1.221985 0.460075 0.221013 2.559570 1.071760 826.19 995.06 1.000 pinvar{all} 0.824411 0.001262 0.756296 0.887993 0.828988 935.01 1086.18 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 -1263.066771 Model 2: PositiveSelection -1263.066771 Model 0: one-ratio -1264.026193 Model 3: discrete -1263.063085 Model 7: beta -1263.3924 Model 8: beta&w>1 -1263.066768 Model 0 vs 1 1.9188439999998081 Model 2 vs 1 0.0 Model 8 vs 7 0.6512640000000829