--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Fri Dec 09 19:06:12 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/442/Zasp52-PX/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/442/Zasp52-PX/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/442/Zasp52-PX/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/442/Zasp52-PX/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -17492.12 -17504.38 2 -17491.51 -17505.99 -------------------------------------- TOTAL -17491.77 -17505.48 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/442/Zasp52-PX/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/442/Zasp52-PX/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/442/Zasp52-PX/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 0.526557 0.000550 0.478922 0.570193 0.526054 1062.77 1199.39 1.000 r(A<->C){all} 0.074316 0.000066 0.058248 0.089894 0.074127 1045.79 1115.35 1.001 r(A<->G){all} 0.227114 0.000219 0.198812 0.256377 0.226743 852.69 921.04 1.000 r(A<->T){all} 0.178340 0.000238 0.147499 0.207461 0.177984 987.49 1072.11 1.000 r(C<->G){all} 0.057667 0.000036 0.046759 0.069950 0.057427 1190.73 1209.92 1.000 r(C<->T){all} 0.383968 0.000338 0.348981 0.419341 0.384073 894.89 935.04 1.000 r(G<->T){all} 0.078595 0.000088 0.060207 0.096855 0.078452 1044.99 1105.94 1.000 pi(A){all} 0.233437 0.000025 0.224114 0.243428 0.233430 1004.00 1070.69 1.000 pi(C){all} 0.334129 0.000030 0.323779 0.345398 0.334045 1118.44 1123.70 1.000 pi(G){all} 0.263307 0.000027 0.252902 0.273093 0.263317 1161.91 1196.19 1.000 pi(T){all} 0.169128 0.000018 0.160294 0.176869 0.169133 1098.34 1115.85 1.000 alpha{1,2} 0.150241 0.000175 0.123181 0.175005 0.149525 1336.99 1376.68 1.000 alpha{3} 5.882425 1.631466 3.586137 8.445575 5.717311 1293.15 1341.47 1.000 pinvar{all} 0.399978 0.000693 0.348814 0.452827 0.400995 1259.90 1309.50 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 -15475.649296 Model 2: PositiveSelection -15475.649296 Model 0: one-ratio -15653.204243 Model 3: discrete -15473.799784 Model 7: beta -15475.812597 Model 8: beta&w>1 -15473.833531 Model 0 vs 1 355.1098940000011 Model 2 vs 1 0.0 Model 8 vs 7 3.9581319999997504