--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Wed Dec 20 02:57:21 WET 2017 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/DGA_B3/NS5_4/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/DGA_B3/NS5_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_4/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/DGA_B3/NS5_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -22261.63 -22306.60 2 -22260.87 -22309.05 -------------------------------------- TOTAL -22261.18 -22308.44 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/DGA_B3/NS5_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_4/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/DGA_B3/NS5_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 6.901823 0.105917 6.310940 7.577892 6.891951 289.93 479.11 1.001 r(A<->C){all} 0.036078 0.000011 0.029510 0.042357 0.035941 639.43 741.41 1.000 r(A<->G){all} 0.187926 0.000084 0.170803 0.205794 0.187432 481.29 548.73 1.001 r(A<->T){all} 0.049003 0.000017 0.041178 0.057169 0.049005 776.80 823.43 1.000 r(C<->G){all} 0.023166 0.000012 0.016130 0.029761 0.023030 809.36 858.00 1.001 r(C<->T){all} 0.674360 0.000143 0.651804 0.698135 0.674677 444.27 486.46 1.000 r(G<->T){all} 0.029466 0.000018 0.021531 0.037837 0.029239 539.00 696.26 1.000 pi(A){all} 0.361198 0.000046 0.347720 0.374376 0.361209 655.80 674.76 1.000 pi(C){all} 0.221810 0.000031 0.211592 0.233131 0.221724 589.21 719.72 1.001 pi(G){all} 0.236345 0.000037 0.225214 0.248683 0.236320 603.10 706.81 1.000 pi(T){all} 0.180646 0.000023 0.171572 0.190194 0.180616 721.33 766.58 1.000 alpha{1,2} 0.197757 0.000065 0.181236 0.212643 0.197520 1260.71 1301.89 1.000 alpha{3} 5.738891 0.740447 4.143632 7.400518 5.668143 923.80 1184.75 1.000 pinvar{all} 0.126623 0.000209 0.099024 0.154283 0.126642 959.77 1028.67 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, -21597.040755