--- EXPERIMENT NOTES --- EXPERIMENT PROPERTIES #Fri Nov 03 10:30:16 WET 2017 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= input.names= mrbayes.params= codeml.params= --- PSRF SUMMARY Estimated marginal likelihoods for runs sampled in files "/opt/ADOPS1/Srevisao1/S3_16Malus/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/Srevisao1/S3_16Malus/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/Srevisao1/S3_16Malus/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat) Run Arithmetic mean Harmonic mean -------------------------------------- 1 -8447.31 -8465.58 2 -8447.21 -8468.32 -------------------------------------- TOTAL -8447.26 -8467.69 -------------------------------------- Model parameter summaries over the runs sampled in files "/opt/ADOPS1/Srevisao1/S3_16Malus/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/Srevisao1/S3_16Malus/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/Srevisao1/S3_16Malus/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat". 95% HPD Interval -------------------- Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+ ------------------------------------------------------------------------------------------------------ TL{all} 1.451176 0.003050 1.344876 1.560936 1.449863 1501.00 1501.00 1.000 r(A<->C){all} 0.118276 0.000120 0.098448 0.141654 0.117703 1034.30 1036.06 1.000 r(A<->G){all} 0.297621 0.000297 0.263423 0.330894 0.297991 975.44 1009.02 1.001 r(A<->T){all} 0.078298 0.000054 0.064985 0.093007 0.078071 973.82 1109.33 1.000 r(C<->G){all} 0.146669 0.000196 0.120430 0.174387 0.146111 784.35 895.74 1.000 r(C<->T){all} 0.282057 0.000282 0.250558 0.315311 0.281764 976.12 1033.75 1.000 r(G<->T){all} 0.077079 0.000065 0.062843 0.094322 0.076976 1053.62 1154.10 1.000 pi(A){all} 0.300031 0.000110 0.280502 0.321041 0.299978 1067.28 1090.79 1.003 pi(C){all} 0.164201 0.000066 0.148123 0.180273 0.164111 979.03 1071.05 1.001 pi(G){all} 0.188529 0.000075 0.172145 0.205610 0.188404 748.55 1027.10 1.001 pi(T){all} 0.347238 0.000122 0.326076 0.368416 0.347348 419.04 711.57 1.000 alpha{1,2} 0.912984 0.016256 0.701384 1.187658 0.894278 1181.69 1300.95 1.000 alpha{3} 1.635071 0.122249 1.061276 2.330674 1.586063 1236.21 1311.76 1.000 pinvar{all} 0.036065 0.000867 0.000006 0.093456 0.028958 1252.37 1367.10 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 -5671.082625 Model 2: PositiveSelection -5628.688889 Model 0: one-ratio -5792.824008 Model 3: discrete -5627.467661 Model 7: beta -5675.259133 Model 8: beta&w>1 -5627.044887 Model 0 vs 1 243.48276599999917 Model 2 vs 1 84.78747199999998 Additional information for M1 vs M2: Naive Empirical Bayes (NEB) analysis Positively selected sites (*: P>95%; **: P>99%) (amino acids refer to 1st sequence: S3_SFBB1) Pr(w>1) post mean +- SE for w 42 N 0.990** 4.384 48 R 1.000** 4.417 52 P 0.992** 4.391 81 L 0.998** 4.411 86 F 0.523 2.786 88 E 0.971* 4.318 128 R 0.924 4.159 136 I 1.000** 4.417 138 T 0.997** 4.409 155 Q 0.614 3.100 184 T 0.604 3.066 202 C 0.825 3.820 218 T 1.000** 4.418 220 E 0.995** 4.400 Bayes Empirical Bayes (BEB) analysis (Yang, Wong & Nielsen 2005. Mol. Biol. Evol. 22:1107-1118) Positively selected sites (*: P>95%; **: P>99%) (amino acids refer to 1st sequence: S3_SFBB1) Pr(w>1) post mean +- SE for w 42 N 0.987* 4.510 +- 0.678 48 R 1.000** 4.559 +- 0.548 52 P 0.990* 4.523 +- 0.649 81 L 0.997** 4.551 +- 0.574 88 E 0.966* 4.439 +- 0.840 128 R 0.897 4.171 +- 1.188 136 I 1.000** 4.559 +- 0.549 138 T 0.997** 4.549 +- 0.579 155 Q 0.570 2.994 +- 1.779 184 T 0.548 2.896 +- 1.765 202 C 0.776 3.723 +- 1.533 218 T 1.000** 4.560 +- 0.545 220 E 0.994** 4.537 +- 0.612 Model 8 vs 7 96.4284919999991 Additional information for M7 vs M8: Naive Empirical Bayes (NEB) analysis Positively selected sites (*: P>95%; **: P>99%) (amino acids refer to 1st sequence: S3_SFBB1) Pr(w>1) post mean +- SE for w 42 N 0.995** 3.867 48 R 1.000** 3.881 52 P 0.996** 3.869 81 L 0.999** 3.878 86 F 0.716 3.037 88 E 0.981* 3.824 128 R 0.962* 3.768 136 I 1.000** 3.881 138 T 0.999** 3.877 155 Q 0.720 3.035 184 T 0.746 3.118 202 C 0.908 3.608 218 T 1.000** 3.881 220 E 0.997** 3.873 Bayes Empirical Bayes (BEB) analysis (Yang, Wong & Nielsen 2005. Mol. Biol. Evol. 22:1107-1118) Positively selected sites (*: P>95%; **: P>99%) (amino acids refer to 1st sequence: S3_SFBB1) Pr(w>1) post mean +- SE for w 42 N 0.994** 3.972 +- 0.583 48 R 1.000** 3.991 +- 0.536 52 P 0.995** 3.976 +- 0.576 81 L 0.999** 3.987 +- 0.547 86 F 0.653 2.853 +- 1.483 88 E 0.978* 3.924 +- 0.698 128 R 0.950 3.828 +- 0.848 136 I 1.000** 3.991 +- 0.536 138 T 0.998** 3.986 +- 0.549 155 Q 0.678 2.961 +- 1.513 184 T 0.695 3.001 +- 1.475 202 C 0.882 3.605 +- 1.109 218 T 1.000** 3.991 +- 0.535 220 E 0.997** 3.981 +- 0.562