--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Fri Nov 25 16:37:32 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/1/26-29-p-PA/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/1/26-29-p-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/26-29-p-PA/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/1/26-29-p-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -6459.17 -6478.37 2 -6458.33 -6475.80 -------------------------------------- TOTAL -6458.66 -6477.75 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/1/26-29-p-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/26-29-p-PA/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/1/26-29-p-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 1.395727 0.006669 1.245451 1.567078 1.392888 1417.92 1459.46 1.000 r(A<->C){all} 0.079864 0.000133 0.057824 0.102788 0.079302 1082.21 1163.84 1.000 r(A<->G){all} 0.237901 0.000491 0.194278 0.280108 0.237253 943.56 959.58 1.000 r(A<->T){all} 0.139145 0.000394 0.099716 0.175798 0.138606 861.41 906.85 1.000 r(C<->G){all} 0.056093 0.000065 0.041772 0.072933 0.055398 1165.38 1217.40 1.000 r(C<->T){all} 0.417615 0.000697 0.366654 0.470134 0.417678 843.37 861.39 1.000 r(G<->T){all} 0.069381 0.000143 0.047029 0.093248 0.068709 1031.95 1042.74 1.000 pi(A){all} 0.231037 0.000097 0.212153 0.249852 0.231068 1122.19 1160.88 1.000 pi(C){all} 0.294517 0.000097 0.276345 0.315336 0.294294 981.31 1117.82 1.000 pi(G){all} 0.264342 0.000098 0.246259 0.284971 0.264201 1146.48 1181.75 1.001 pi(T){all} 0.210103 0.000078 0.193861 0.228494 0.209995 1124.06 1132.98 1.001 alpha{1,2} 0.124657 0.000085 0.106656 0.142731 0.124103 1165.41 1314.09 1.000 alpha{3} 4.077650 0.827212 2.471403 5.978732 3.976993 759.08 1063.61 1.000 pinvar{all} 0.298656 0.000966 0.236553 0.357737 0.299561 1095.58 1265.72 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 -6059.250602 Model 2: PositiveSelection -6059.250602 Model 0: one-ratio -6101.198072 Model 3: discrete -6025.977293 Model 7: beta -6026.099343 Model 8: beta&w>1 -6026.10085 Model 0 vs 1 83.89494000000013 Model 2 vs 1 0.0 Model 8 vs 7 0.003013999999893713