--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Mon Feb 15 19:47:10 WET 2016 codeml.models= 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/Z_B1/Zika-NS3_3/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/Z_B1/Zika-NS3_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/Z_B1/Zika-NS3_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/Z_B1/Zika-NS3_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -5059.60 -5122.33 2 -5058.07 -5119.74 -------------------------------------- TOTAL -5058.56 -5121.71 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/Z_B1/Zika-NS3_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/Z_B1/Zika-NS3_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/Z_B1/Zika-NS3_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} 0.771744 0.004514 0.647474 0.904792 0.768009 585.84 610.81 1.000 r(A<->C){all} 0.028299 0.000054 0.015036 0.042817 0.027756 819.90 887.88 1.000 r(A<->G){all} 0.169378 0.000548 0.130012 0.219954 0.167865 475.46 596.00 1.000 r(A<->T){all} 0.037409 0.000092 0.019134 0.056227 0.036592 854.57 880.90 1.001 r(C<->G){all} 0.012462 0.000030 0.002867 0.022978 0.011892 820.39 865.60 1.000 r(C<->T){all} 0.726158 0.000852 0.672259 0.783187 0.727329 399.08 484.95 1.000 r(G<->T){all} 0.026294 0.000069 0.011298 0.042457 0.025450 708.20 735.01 1.000 pi(A){all} 0.281580 0.000096 0.262478 0.300912 0.281572 1017.03 1044.41 1.000 pi(C){all} 0.232508 0.000077 0.214731 0.249785 0.232481 980.17 1119.45 1.000 pi(G){all} 0.278689 0.000094 0.260907 0.298217 0.278285 835.32 921.59 1.000 pi(T){all} 0.207222 0.000072 0.190225 0.223361 0.207208 1088.20 1205.47 1.000 alpha{1,2} 0.094882 0.000339 0.061249 0.127996 0.097164 604.26 674.08 1.000 alpha{3} 4.536933 1.206159 2.489765 6.534293 4.441817 1312.61 1401.98 1.000 pinvar{all} 0.279117 0.002314 0.184660 0.369486 0.282047 549.95 748.35 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: One dN/dS ratio for branches, -4771.449896