--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Sun Oct 01 00:01:48 WEST 2017 codeml.models=0 1 2 3 7 8 mrbayes.mpich= mrbayes.ngen=1000000 tcoffee.alignMethod=MUSCLE tcoffee.params= tcoffee.maxSeqs=0 codeml.bin=codeml mrbayes.tburnin=2500 codeml.dir=/usr/bin/ input.sequences= mrbayes.pburnin=2500 mrbayes.bin=mb tcoffee.bin=t_coffee mrbayes.dir= tcoffee.dir= tcoffee.minScore=3 input.fasta=/opt/ADOPS/DATA/Zika/Batch_1_ADOPS/Zika-pr/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/DATA/Zika/Batch_1_ADOPS/Zika-pr/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/Batch_1_ADOPS/Zika-pr/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/DATA/Zika/Batch_1_ADOPS/Zika-pr/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -1481.10 -1543.08 2 -1485.10 -1536.53 -------------------------------------- TOTAL -1481.77 -1542.39 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/DATA/Zika/Batch_1_ADOPS/Zika-pr/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/Batch_1_ADOPS/Zika-pr/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/DATA/Zika/Batch_1_ADOPS/Zika-pr/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 14.231963 1.678351 11.762970 16.860310 14.190420 933.64 1023.20 1.001 r(A<->C){all} 0.065258 0.000499 0.022748 0.108233 0.063034 625.73 676.05 1.000 r(A<->G){all} 0.279692 0.003585 0.172386 0.401717 0.277969 269.74 386.90 1.003 r(A<->T){all} 0.038043 0.000241 0.011182 0.068969 0.036023 717.87 734.73 1.000 r(C<->G){all} 0.010499 0.000071 0.000018 0.027123 0.008486 714.40 788.34 1.000 r(C<->T){all} 0.582008 0.004420 0.450093 0.709147 0.583276 273.11 365.03 1.003 r(G<->T){all} 0.024501 0.000118 0.005836 0.045555 0.022937 730.84 739.12 1.002 pi(A){all} 0.280625 0.000597 0.236761 0.332002 0.279752 766.99 917.04 1.000 pi(C){all} 0.205546 0.000434 0.165678 0.246583 0.204474 483.94 728.75 1.001 pi(G){all} 0.288735 0.000589 0.243707 0.338181 0.288211 1028.29 1062.03 1.002 pi(T){all} 0.225094 0.000508 0.184942 0.272649 0.224367 712.00 824.16 1.000 alpha{1,2} 0.083988 0.000026 0.073554 0.093405 0.083735 1185.65 1189.14 1.001 alpha{3} 0.320268 0.002857 0.251928 0.429815 0.318345 186.78 703.29 1.014 pinvar{all} 0.178474 0.003923 0.054999 0.295093 0.179513 885.70 994.27 1.004 ------------------------------------------------------------------------------------------------------ * 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 -1242.129723 Model 2: PositiveSelection -1242.13823 Model 0: one-ratio -1242.13823 Model 3: discrete -1237.217799 Model 7: beta -1237.774059 Model 8: beta&w>1 -1237.774377 Model 0 vs 1 0.017014000000017404 Model 2 vs 1 0.017014000000017404 Model 8 vs 7 6.359999997584964E-4