--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Mon Feb 15 18:40:10 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_1/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/Z_B1/Zika-NS3_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/Z_B1/Zika-NS3_1/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_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -4290.12 -4344.83 2 -4288.75 -4358.34 -------------------------------------- TOTAL -4289.22 -4357.65 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/Z_B1/Zika-NS3_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/Z_B1/Zika-NS3_1/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_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 0.903752 0.012935 0.705603 1.143963 0.891314 387.28 420.76 1.000 r(A<->C){all} 0.019023 0.000052 0.006685 0.033874 0.018367 521.16 609.38 1.001 r(A<->G){all} 0.268087 0.001994 0.189393 0.362198 0.266993 310.27 431.65 1.000 r(A<->T){all} 0.015838 0.000057 0.002340 0.030218 0.014681 541.64 707.15 1.000 r(C<->G){all} 0.006916 0.000018 0.000484 0.015554 0.006160 873.43 891.48 1.000 r(C<->T){all} 0.664737 0.002362 0.563381 0.752409 0.665257 294.56 395.27 1.000 r(G<->T){all} 0.025398 0.000080 0.009583 0.043789 0.024597 750.64 818.10 1.000 pi(A){all} 0.281122 0.000099 0.261962 0.300419 0.281192 1050.74 1182.86 1.000 pi(C){all} 0.230149 0.000086 0.212020 0.247698 0.230138 881.59 970.07 1.000 pi(G){all} 0.280475 0.000096 0.261942 0.300056 0.280172 1075.68 1127.92 1.002 pi(T){all} 0.208255 0.000075 0.192267 0.225421 0.208298 1044.24 1169.25 1.000 alpha{1,2} 0.041711 0.000522 0.000168 0.075718 0.043404 1088.72 1108.40 1.000 alpha{3} 3.603297 0.972820 1.874561 5.533610 3.468452 1183.99 1279.52 1.000 pinvar{all} 0.451326 0.000972 0.389857 0.510911 0.451929 1346.32 1360.00 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, -4021.142799