--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Sat Nov 19 01:15:13 WET 2016 codeml.models=0 1 2 3 7 8 mrbayes.mpich= mrbayes.ngen=1000000 tcoffee.alignMethod=CLUSTALW2 tcoffee.params= tcoffee.maxSeqs=0 codeml.bin=codeml mrbayes.tburnin=2500 codeml.dir= input.sequences= mrbayes.pburnin=2500 mrbayes.bin=mb_adops tcoffee.bin=t_coffee_ADOPS mrbayes.dir=/usr/bin/ tcoffee.dir= tcoffee.minScore=3 input.fasta=/opt/ADOPS/274/Hsc70-5-PA/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/274/Hsc70-5-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/274/Hsc70-5-PA/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/274/Hsc70-5-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -6762.67 -6778.60 2 -6762.83 -6778.26 -------------------------------------- TOTAL -6762.75 -6778.44 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/274/Hsc70-5-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/274/Hsc70-5-PA/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/274/Hsc70-5-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 1.142365 0.004460 1.018508 1.279946 1.141402 1261.32 1367.34 1.001 r(A<->C){all} 0.063453 0.000106 0.045425 0.085048 0.063129 1075.06 1109.57 1.000 r(A<->G){all} 0.239397 0.000515 0.195501 0.285261 0.238781 837.57 890.22 1.001 r(A<->T){all} 0.108232 0.000373 0.072535 0.148774 0.106861 811.58 850.21 1.000 r(C<->G){all} 0.029086 0.000030 0.018373 0.039906 0.028819 1075.69 1189.47 1.001 r(C<->T){all} 0.486673 0.000713 0.432994 0.536510 0.485808 798.22 858.80 1.000 r(G<->T){all} 0.073160 0.000124 0.052147 0.095207 0.072566 967.06 1054.43 1.001 pi(A){all} 0.220938 0.000077 0.204258 0.237830 0.220798 969.31 1098.05 1.000 pi(C){all} 0.295086 0.000084 0.277393 0.312273 0.295085 966.74 1102.95 1.000 pi(G){all} 0.289673 0.000094 0.271855 0.308754 0.289796 1177.93 1245.48 1.000 pi(T){all} 0.194302 0.000059 0.178792 0.208944 0.194406 1123.97 1131.86 1.000 alpha{1,2} 0.084933 0.000049 0.071485 0.098219 0.084758 1369.91 1431.08 1.000 alpha{3} 4.574438 1.022920 2.774277 6.579811 4.484073 1487.34 1494.17 1.000 pinvar{all} 0.358231 0.000744 0.304625 0.411738 0.358489 1091.67 1247.34 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 -6298.787654 Model 2: PositiveSelection -6298.787654 Model 0: one-ratio -6338.704008 Model 3: discrete -6288.661124 Model 7: beta -6292.126465 Model 8: beta&w>1 -6289.117973 Model 0 vs 1 79.83270799999991 Model 2 vs 1 0.0 Model 8 vs 7 6.016983999999866 Additional information for M7 vs M8: Naive Empirical Bayes (NEB) analysis Positively selected sites (*: P>95%; **: P>99%) (amino acids refer to 1st sequence: D_melanogaster_Hsc70-5-PA) Pr(w>1) post mean +- SE for w 660 N 0.995** 0.996 661 A 0.721 0.760 Bayes Empirical Bayes (BEB) analysis (Yang, Wong & Nielsen 2005. Mol. Biol. Evol. 22:1107-1118) Positively selected sites (*: P>95%; **: P>99%) (amino acids refer to 1st sequence: D_melanogaster_Hsc70-5-PA) Pr(w>1) post mean +- SE for w 660 N 0.820 1.431 +- 0.511 661 A 0.640 1.214 +- 0.661 662 G 0.581 1.113 +- 0.721