--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Sun May 13 01:28:00 WEST 2018 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= 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/ADOPS1/DNG_N2/NS3_1/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS1/DNG_N2/NS3_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/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/ADOPS1/DNG_N2/NS3_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -14034.54 -14081.15 2 -14034.65 -14078.23 -------------------------------------- TOTAL -14034.59 -14080.51 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS1/DNG_N2/NS3_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/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/ADOPS1/DNG_N2/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} 7.996487 0.185794 7.149314 8.846762 7.988390 543.38 644.09 1.001 r(A<->C){all} 0.038383 0.000021 0.029729 0.047227 0.038353 721.52 800.96 1.000 r(A<->G){all} 0.188100 0.000142 0.165009 0.211106 0.187959 356.37 419.35 1.000 r(A<->T){all} 0.040573 0.000023 0.031738 0.050365 0.040334 797.30 824.24 1.002 r(C<->G){all} 0.016096 0.000014 0.008840 0.023246 0.015875 727.53 780.20 1.002 r(C<->T){all} 0.692003 0.000223 0.661887 0.718734 0.692027 322.81 410.10 1.001 r(G<->T){all} 0.024844 0.000022 0.015476 0.033641 0.024562 825.30 840.93 1.000 pi(A){all} 0.357829 0.000064 0.342153 0.373484 0.357717 725.17 755.45 1.000 pi(C){all} 0.216198 0.000043 0.204034 0.229648 0.216178 692.29 705.08 1.000 pi(G){all} 0.231022 0.000050 0.218207 0.245644 0.230743 677.20 695.85 1.001 pi(T){all} 0.194951 0.000037 0.182680 0.206027 0.194944 669.47 715.30 1.000 alpha{1,2} 0.157489 0.000045 0.144040 0.170021 0.157265 1175.26 1249.58 1.000 alpha{3} 5.665703 0.830564 4.096319 7.577616 5.564216 1224.90 1282.90 1.001 pinvar{all} 0.124441 0.000298 0.091971 0.159184 0.124127 1179.28 1302.67 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 1: NearlyNeutral -13230.463408 Model 2: PositiveSelection -13230.463408 Model 0: one-ratio -13264.227654 Model 3: discrete -13096.500061 Model 7: beta -13083.261299 Model 8: beta&w>1 -13082.522104 Model 0 vs 1 67.52849200000128 Model 2 vs 1 0.0 Model 8 vs 7 1.4783900000002177