--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Tue Oct 31 17:22:04 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/Srevisao/S10_17Malus/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/Srevisao/S10_17Malus/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/Srevisao/S10_17Malus/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -8187.19 -8205.96
2 -8186.69 -8207.35
--------------------------------------
TOTAL -8186.91 -8206.88
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/Srevisao/S10_17Malus/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/Srevisao/S10_17Malus/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/Srevisao/S10_17Malus/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 1.500904 0.003399 1.387379 1.612350 1.498621 1501.00 1501.00 1.001
r(A<->C){all} 0.116159 0.000127 0.093586 0.137136 0.115918 797.50 966.84 1.000
r(A<->G){all} 0.304161 0.000312 0.269931 0.337823 0.304084 792.76 866.17 1.000
r(A<->T){all} 0.073605 0.000047 0.060579 0.086789 0.073365 1172.72 1191.28 1.001
r(C<->G){all} 0.153546 0.000208 0.127365 0.183627 0.153141 915.35 921.41 1.000
r(C<->T){all} 0.267489 0.000280 0.233452 0.297932 0.267719 748.52 830.83 1.001
r(G<->T){all} 0.085039 0.000075 0.068658 0.102788 0.084557 1049.55 1083.71 1.000
pi(A){all} 0.298176 0.000111 0.276450 0.318650 0.298086 981.00 1019.93 1.001
pi(C){all} 0.170038 0.000068 0.154566 0.186342 0.170000 806.43 928.97 1.000
pi(G){all} 0.188570 0.000075 0.171619 0.204928 0.188317 826.42 925.19 1.000
pi(T){all} 0.343216 0.000125 0.322118 0.364739 0.343439 927.70 969.61 1.000
alpha{1,2} 0.945389 0.018856 0.705820 1.211655 0.929334 1247.03 1299.01 1.000
alpha{3} 1.734228 0.159330 1.094733 2.534816 1.669443 1214.91 1264.17 1.000
pinvar{all} 0.035114 0.000818 0.000015 0.091155 0.028601 1225.86 1258.89 1.001
------------------------------------------------------------------------------------------------------
* 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 -4760.325842
Model 2: PositiveSelection -4722.33529
Model 0: one-ratio -4884.237773
Model 3: discrete -4722.131359
Model 7: beta -4771.204726
Model 8: beta&w>1 -4724.825834
Model 0 vs 1 247.82386199999928
Model 2 vs 1 75.98110400000041
Additional information for M1 vs M2:
Naive Empirical Bayes (NEB) analysis
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: S10_SFBB1)
Pr(w>1) post mean +- SE for w
10 N 0.997** 3.746
16 R 0.999** 3.752
20 P 0.999** 3.753
49 L 0.997** 3.746
54 F 0.815 3.245
56 E 0.958* 3.638
96 R 0.867 3.387
104 I 0.998** 3.749
106 T 0.999** 3.751
123 Q 0.644 2.773
152 T 0.898 3.472
167 E 0.754 3.077
170 C 0.987* 3.717
186 T 1.000** 3.754
188 E 0.947 3.609
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: S10_SFBB1)
Pr(w>1) post mean +- SE for w
10 N 0.996** 3.847 +- 0.534
16 R 0.999** 3.856 +- 0.512
20 P 0.999** 3.857 +- 0.509
49 L 0.996** 3.849 +- 0.531
54 F 0.749 3.090 +- 1.277
56 E 0.947 3.706 +- 0.807
96 R 0.818 3.307 +- 1.172
104 I 0.998** 3.852 +- 0.522
106 T 0.998** 3.854 +- 0.516
123 Q 0.585 2.641 +- 1.432
152 T 0.865 3.456 +- 1.075
167 E 0.676 2.870 +- 1.347
170 C 0.983* 3.809 +- 0.623
186 T 1.000** 3.859 +- 0.504
188 E 0.930 3.654 +- 0.871
Model 8 vs 7 92.75778399999945
Additional information for M7 vs M8:
Naive Empirical Bayes (NEB) analysis
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: S10_SFBB1)
Pr(w>1) post mean +- SE for w
10 N 0.999** 3.249
11 H 0.520 2.092
16 R 1.000** 3.250
20 P 1.000** 3.250
49 L 0.999** 3.248
54 F 0.941 3.111
56 E 0.981* 3.205
58 G 0.524 2.101
69 A 0.706 2.547
81 G 0.686 2.494
93 Q 0.676 2.466
96 R 0.953* 3.138
104 I 0.999** 3.249
106 T 1.000** 3.249
123 Q 0.798 2.761
152 T 0.959* 3.154
167 E 0.918 3.057
170 C 0.995** 3.238
186 T 1.000** 3.250
188 E 0.979* 3.202
216 K 0.607 2.307
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: S10_SFBB1)
Pr(w>1) post mean +- SE for w
10 N 0.999** 3.158 +- 0.573
11 H 0.544 1.983 +- 1.115
16 R 1.000** 3.160 +- 0.570
20 P 1.000** 3.160 +- 0.569
49 L 0.999** 3.157 +- 0.574
54 F 0.912 2.923 +- 0.820
56 E 0.976* 3.100 +- 0.662
58 G 0.547 1.993 +- 1.123
69 A 0.685 2.333 +- 1.092
81 G 0.671 2.304 +- 1.114
93 Q 0.664 2.292 +- 1.129
96 R 0.933 2.980 +- 0.780
104 I 0.999** 3.158 +- 0.572
106 T 0.999** 3.159 +- 0.570
123 Q 0.775 2.580 +- 1.059
138 Y 0.520 1.923 +- 1.080
152 T 0.946 3.020 +- 0.750
167 E 0.881 2.839 +- 0.878
170 C 0.993** 3.144 +- 0.596
186 T 1.000** 3.161 +- 0.568
188 E 0.973* 3.090 +- 0.670
216 K 0.607 2.135 +- 1.106
