--- 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
