--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Thu May 03 23:16:31 WEST 2018 codeml.models= 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=/usr/bin/ tcoffee.dir= tcoffee.minScore=3 input.fasta=/opt/ADOPS/DNGB3/NS5_5/input.fasta input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS/DNGB3/NS5_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DNGB3/NS5_5/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/DNGB3/NS5_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -20308.63 -20359.61 2 -20311.87 -20346.48 -------------------------------------- TOTAL -20309.28 -20358.92 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS/DNGB3/NS5_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DNGB3/NS5_5/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/DNGB3/NS5_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 6.531718 0.109004 5.914085 7.197690 6.521873 410.83 417.93 1.004 r(A<->C){all} 0.042863 0.000016 0.035378 0.050781 0.042826 728.28 790.35 1.000 r(A<->G){all} 0.185676 0.000095 0.166779 0.204497 0.185822 443.92 445.33 1.000 r(A<->T){all} 0.043253 0.000020 0.034707 0.052235 0.043331 500.84 653.51 1.000 r(C<->G){all} 0.028639 0.000017 0.020885 0.036806 0.028488 777.07 839.15 1.000 r(C<->T){all} 0.676374 0.000172 0.652171 0.703560 0.676458 396.06 407.46 1.000 r(G<->T){all} 0.023194 0.000019 0.014690 0.031119 0.023106 677.38 707.56 1.000 pi(A){all} 0.356881 0.000049 0.342716 0.370494 0.357050 809.95 824.91 1.000 pi(C){all} 0.219329 0.000029 0.209532 0.230181 0.219213 828.70 864.42 1.001 pi(G){all} 0.240595 0.000038 0.229385 0.253429 0.240683 693.14 763.98 1.003 pi(T){all} 0.183195 0.000027 0.173244 0.193327 0.183210 601.17 649.10 1.000 alpha{1,2} 0.186403 0.000060 0.170810 0.201248 0.186128 1135.38 1240.32 1.000 alpha{3} 5.000369 0.604936 3.613205 6.474755 4.910508 1236.26 1314.68 1.000 pinvar{all} 0.122852 0.000240 0.092680 0.152978 0.122416 1231.02 1232.72 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: One dN/dS ratio for branches, -17822.477632