--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Wed Feb 17 00:56:01 WET 2016 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=/usr/bin/ tcoffee.dir= tcoffee.minScore=3 input.fasta=/opt/ADOPS/DATA/Zika/B4_A/Zika-NS5_3/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/DATA/Zika/B4_A/Zika-NS5_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B4_A/Zika-NS5_3/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/B4_A/Zika-NS5_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -9155.96 -9247.68 2 -9154.07 -9238.00 -------------------------------------- TOTAL -9154.62 -9246.99 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/DATA/Zika/B4_A/Zika-NS5_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B4_A/Zika-NS5_3/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/B4_A/Zika-NS5_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 1.119654 0.003470 1.003076 1.232045 1.117332 714.32 750.83 1.000 r(A<->C){all} 0.023124 0.000020 0.014547 0.031631 0.022844 599.65 717.76 1.000 r(A<->G){all} 0.215361 0.000427 0.175094 0.255568 0.214306 356.15 386.78 1.000 r(A<->T){all} 0.020253 0.000024 0.011388 0.030361 0.019853 630.81 701.16 1.001 r(C<->G){all} 0.003003 0.000003 0.000164 0.006245 0.002767 795.64 818.83 1.000 r(C<->T){all} 0.716584 0.000547 0.670195 0.760399 0.717576 334.65 360.29 1.000 r(G<->T){all} 0.021675 0.000020 0.013935 0.031223 0.021332 682.28 718.14 1.000 pi(A){all} 0.280519 0.000062 0.264520 0.295282 0.280289 924.08 1014.58 1.002 pi(C){all} 0.227629 0.000052 0.213053 0.241120 0.227444 908.07 995.75 1.002 pi(G){all} 0.295418 0.000068 0.278933 0.311877 0.295459 979.54 1032.45 1.000 pi(T){all} 0.196434 0.000045 0.182725 0.208846 0.196381 684.82 887.79 1.000 alpha{1,2} 0.116468 0.000068 0.101205 0.133228 0.116085 1166.94 1190.04 1.000 alpha{3} 5.063851 1.150929 3.116586 7.164913 4.963227 1238.93 1344.24 1.000 pinvar{all} 0.303283 0.000726 0.248076 0.353593 0.303840 724.25 913.15 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 -8535.980608 Model 2: PositiveSelection -8535.980632 Model 0: one-ratio -8571.24262 Model 3: discrete -8529.52584 Model 7: beta -8529.594999 Model 8: beta&w>1 -8529.595061 Model 0 vs 1 70.5240240000021 Model 2 vs 1 4.8000001697801054E-5 Model 8 vs 7 1.2399999832268804E-4