--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Tue Nov 13 23:59:33 GMT 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=/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/repeat/ns3_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/repeat/ns3_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/repeat/ns3_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -15023.98 -15061.84 2 -15025.14 -15063.44 -------------------------------------- TOTAL -15024.40 -15062.93 -------------------------------------- Model parameter summaries over the runs sampled in files "/data/repeat/ns3_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/repeat/ns3_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/repeat/ns3_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} 8.142768 0.178056 7.312768 8.917170 8.134761 508.04 750.36 1.000 r(A<->C){all} 0.036531 0.000017 0.028414 0.044292 0.036486 729.96 854.62 1.000 r(A<->G){all} 0.199935 0.000145 0.176875 0.224298 0.199886 378.33 429.99 1.003 r(A<->T){all} 0.040589 0.000020 0.031458 0.048652 0.040562 502.64 689.70 1.000 r(C<->G){all} 0.019217 0.000014 0.012086 0.026592 0.019035 856.59 906.08 1.000 r(C<->T){all} 0.684672 0.000215 0.656985 0.714113 0.684637 428.79 441.27 1.002 r(G<->T){all} 0.019055 0.000017 0.011421 0.027215 0.018816 614.70 687.90 1.000 pi(A){all} 0.356276 0.000066 0.339888 0.371882 0.356212 638.40 744.26 1.000 pi(C){all} 0.219145 0.000044 0.206394 0.232256 0.219122 517.30 542.83 1.000 pi(G){all} 0.228976 0.000049 0.215660 0.243032 0.228948 561.05 623.81 1.001 pi(T){all} 0.195603 0.000037 0.184025 0.208137 0.195576 558.82 663.26 1.001 alpha{1,2} 0.161910 0.000051 0.147876 0.175571 0.161671 1094.53 1252.79 1.000 alpha{3} 5.358050 0.676307 3.913713 7.067442 5.279592 1371.88 1436.44 1.000 pinvar{all} 0.115719 0.000300 0.082447 0.150216 0.115379 1082.58 1171.53 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 -14400.462733 Model 2: PositiveSelection -14400.462734 Model 0: one-ratio -14440.654751 Model 3: discrete -14263.518451 Model 7: beta -14266.551944 Model 8: beta&w>1 -14266.558115 Model 0 vs 1 80.38403599999947 Model 2 vs 1 2.0000006770715117E-6 Model 8 vs 7 0.01234199999817065