--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Sat Jan 19 04:18:02 GMT 2019 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=/opt/mrbayes_3.2.2/src tcoffee.dir= tcoffee.minScore=3 input.fasta= input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/data/A_NS4B_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/A_NS4B_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.run2.p": (Use the harmonic mean for Bayes factor comparisons of models) (Values are saved to the file /data/A_NS4B_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -7418.45 -7456.04 2 -7418.08 -7457.16 -------------------------------------- TOTAL -7418.25 -7456.75 -------------------------------------- Model parameter summaries over the runs sampled in files "/data/A_NS4B_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/A_NS4B_4/Muscle/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 "/data/A_NS4B_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 7.590823 0.214131 6.706226 8.490758 7.584121 868.41 908.65 1.000 r(A<->C){all} 0.036110 0.000036 0.024139 0.047987 0.035873 614.37 757.38 1.000 r(A<->G){all} 0.221680 0.000318 0.188398 0.257473 0.221338 382.68 504.75 1.000 r(A<->T){all} 0.054762 0.000051 0.041082 0.068839 0.054573 718.27 771.60 1.000 r(C<->G){all} 0.041638 0.000052 0.027495 0.055087 0.041212 865.25 907.53 1.000 r(C<->T){all} 0.620749 0.000478 0.576920 0.661524 0.620833 410.42 510.14 1.000 r(G<->T){all} 0.025060 0.000039 0.013636 0.037554 0.024813 586.14 669.90 1.001 pi(A){all} 0.328907 0.000154 0.306444 0.355033 0.328711 861.38 901.38 1.000 pi(C){all} 0.236693 0.000107 0.215692 0.256676 0.236531 756.15 827.90 1.000 pi(G){all} 0.214890 0.000118 0.194189 0.236089 0.214773 704.42 746.15 1.001 pi(T){all} 0.219510 0.000102 0.199966 0.239241 0.219327 617.88 661.69 1.000 alpha{1,2} 0.208312 0.000229 0.181524 0.238773 0.206892 1257.04 1335.81 1.000 alpha{3} 4.676802 0.762977 3.075306 6.410978 4.600007 1425.82 1463.41 1.000 pinvar{all} 0.125559 0.000726 0.073897 0.177822 0.124561 1282.91 1356.19 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 -6939.894242 Model 2: PositiveSelection -6939.894242 Model 0: one-ratio -6982.542395 Model 3: discrete -6873.849457 Model 7: beta -6877.893161 Model 8: beta&w>1 -6877.895608 Model 0 vs 1 85.29630600000019 Model 2 vs 1 0.0 Model 8 vs 7 0.004893999999694643