--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Fri Nov 03 21:02:43 WET 2017
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=
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/revmuscle/S24/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/revmuscle/S24/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/revmuscle/S24/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -7299.74         -7324.22
2      -7299.62         -7320.89
--------------------------------------
TOTAL    -7299.68         -7323.56
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/revmuscle/S24/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/revmuscle/S24/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/revmuscle/S24/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         1.526172    0.003975    1.401025    1.646728    1.525765   1490.11   1495.55    1.000
r(A<->C){all}   0.119419    0.000141    0.097322    0.143094    0.118867    607.85    769.50    1.000
r(A<->G){all}   0.298933    0.000331    0.263852    0.334001    0.298466    858.48    869.35    1.000
r(A<->T){all}   0.074262    0.000057    0.060008    0.089341    0.073752   1055.82   1203.40    1.001
r(C<->G){all}   0.154746    0.000244    0.125397    0.185798    0.154099    829.69    890.90    1.000
r(C<->T){all}   0.267171    0.000302    0.233586    0.301605    0.266739    630.14    690.37    1.000
r(G<->T){all}   0.085468    0.000085    0.067959    0.103200    0.084985    842.46    960.21    1.000
pi(A){all}      0.293028    0.000116    0.272573    0.314161    0.293069   1065.70   1135.79    1.000
pi(C){all}      0.174873    0.000076    0.157566    0.191642    0.174665   1175.14   1176.77    1.000
pi(G){all}      0.196732    0.000086    0.179797    0.216285    0.196555    968.97   1078.30    1.000
pi(T){all}      0.335367    0.000132    0.311555    0.356059    0.335312   1036.07   1162.47    1.000
alpha{1,2}      0.763396    0.014241    0.566847    1.016668    0.747600   1099.68   1291.73    1.000
alpha{3}        2.360759    0.398417    1.274220    3.588140    2.256517   1233.25   1289.72    1.000
pinvar{all}     0.048625    0.001381    0.000029    0.118790    0.040283   1053.27   1192.57    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	-3367.119516
Model 2: PositiveSelection	-3344.39726
Model 0: one-ratio	-3441.109162
Model 3: discrete	-3344.185046
Model 7: beta	-3369.288535
Model 8: beta&w>1	-3343.969934


Model 0 vs 1	147.979292

Model 2 vs 1	45.44451200000003

Additional information for M1 vs M2:
Naive Empirical Bayes (NEB) analysis
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: S24_SFBB1)

            Pr(w>1)     post mean +- SE for w

     2 E      0.983*        4.288
    50 I      0.999**       4.344
    52 T      0.999**       4.344
    69 Q      0.530         2.773
    84 Y      0.544         2.820
   113 E      0.970*        4.246
   115 C      0.966*        4.232
   131 T      1.000**       4.345
   133 E      0.897         4.001

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: S24_SFBB1)

            Pr(w>1)     post mean +- SE for w

     2 E      0.980*        4.516 +- 0.959
    50 I      0.999**       4.584 +- 0.829
    52 T      0.999**       4.584 +- 0.828
   113 E      0.950         4.378 +- 1.101
   115 C      0.955*        4.416 +- 1.088
   131 T      1.000**       4.586 +- 0.825
   133 E      0.855         4.013 +- 1.437


Model 8 vs 7	50.63720199999989

Additional information for M7 vs M8:
Naive Empirical Bayes (NEB) analysis
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: S24_SFBB1)

            Pr(w>1)     post mean +- SE for w

     2 E      0.988*        3.744
    42 R      0.641         2.751
    50 I      1.000**       3.778
    52 T      1.000**       3.778
    69 Q      0.662         2.806
    84 Y      0.728         3.003
   113 E      0.984*        3.733
   115 C      0.979*        3.719
   131 T      1.000**       3.778
   133 E      0.941         3.610

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: S24_SFBB1)

            Pr(w>1)     post mean +- SE for w

     2 E      0.986*        3.942 +- 0.866
    42 R      0.550         2.458 +- 1.513
    50 I      0.999**       3.981 +- 0.796
    52 T      1.000**       3.981 +- 0.795
    69 Q      0.603         2.671 +- 1.572
    84 Y      0.637         2.736 +- 1.497
   113 E      0.975*        3.896 +- 0.910
   115 C      0.974*        3.898 +- 0.923
   131 T      1.000**       3.982 +- 0.795
   133 E      0.917         3.700 +- 1.126