--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Sun Jul 15 16:39:02 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_N3/prM_4/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS1/DNG_N3/prM_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/prM_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/ADOPS1/DNG_N3/prM_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -4194.45 -4234.85 2 -4190.64 -4240.11 -------------------------------------- TOTAL -4191.31 -4239.42 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS1/DNG_N3/prM_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/prM_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/ADOPS1/DNG_N3/prM_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} 6.997234 0.283086 5.958965 8.023488 6.983296 643.34 942.66 1.000 r(A<->C){all} 0.040342 0.000074 0.024139 0.057363 0.039951 906.65 955.27 1.000 r(A<->G){all} 0.189127 0.000497 0.145193 0.229938 0.189010 543.26 647.83 1.000 r(A<->T){all} 0.060547 0.000121 0.038913 0.081604 0.060061 950.94 961.27 1.000 r(C<->G){all} 0.022341 0.000056 0.008633 0.036798 0.021847 792.87 904.59 1.001 r(C<->T){all} 0.651113 0.000797 0.596612 0.706436 0.651107 477.95 648.26 1.000 r(G<->T){all} 0.036531 0.000101 0.018678 0.056452 0.035896 790.10 830.00 1.001 pi(A){all} 0.300643 0.000217 0.272338 0.328294 0.300586 912.73 976.66 1.000 pi(C){all} 0.250444 0.000180 0.225358 0.278139 0.250259 762.65 763.96 1.000 pi(G){all} 0.239497 0.000216 0.210454 0.266969 0.239141 821.35 835.78 1.000 pi(T){all} 0.209416 0.000140 0.186480 0.233125 0.209175 862.16 941.38 1.000 alpha{1,2} 0.196338 0.000267 0.164671 0.228289 0.195265 1149.25 1242.09 1.000 alpha{3} 3.724688 0.688380 2.257511 5.427526 3.624487 1402.51 1451.76 1.000 pinvar{all} 0.047002 0.000788 0.000020 0.097018 0.044753 1410.60 1455.80 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 -3953.082254 Model 2: PositiveSelection -3953.082254 Model 0: one-ratio -3966.810545 Model 3: discrete -3919.447424 Model 7: beta -3921.588518 Model 8: beta&w>1 -3921.589525 Model 0 vs 1 27.4565819999998 Model 2 vs 1 0.0 Model 8 vs 7 0.002013999999689986