--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Sat Jun 16 11:12:55 WEST 2018
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=/opt/ADOPS1/DNG_A2/prM_5/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_A2/prM_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A2/prM_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/ADOPS1/DNG_A2/prM_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -4434.04         -4481.02
2      -4430.78         -4477.94
--------------------------------------
TOTAL    -4431.44         -4480.37
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_A2/prM_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A2/prM_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/ADOPS1/DNG_A2/prM_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}         6.260804    0.204678    5.380550    7.143599    6.260414    950.79    996.33    1.000
r(A<->C){all}   0.046927    0.000076    0.032047    0.065087    0.046291    606.09    758.47    1.000
r(A<->G){all}   0.190561    0.000483    0.151254    0.235823    0.189495    606.07    615.91    1.000
r(A<->T){all}   0.048055    0.000089    0.030364    0.067317    0.047710    785.90    892.30    1.001
r(C<->G){all}   0.028361    0.000059    0.013864    0.043423    0.027956    653.47    768.80    1.000
r(C<->T){all}   0.646253    0.000807    0.587387    0.695705    0.647031    594.96    604.15    1.000
r(G<->T){all}   0.039844    0.000097    0.020580    0.057904    0.039235    691.98    812.72    1.000
pi(A){all}      0.299448    0.000217    0.268872    0.326821    0.299310    913.72    950.96    1.000
pi(C){all}      0.250514    0.000176    0.224815    0.275948    0.250458    847.17    901.01    1.000
pi(G){all}      0.244273    0.000198    0.216975    0.271861    0.243965    652.61    789.45    1.000
pi(T){all}      0.205765    0.000143    0.182493    0.229103    0.205519    842.48    867.04    1.000
alpha{1,2}      0.223745    0.000396    0.185657    0.262563    0.222406   1149.65   1202.88    1.000
alpha{3}        3.933662    0.785960    2.368686    5.699515    3.815768   1372.77   1404.03    1.000
pinvar{all}     0.047295    0.000818    0.000165    0.098383    0.044923    986.51   1173.32    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	-4274.171771
Model 2: PositiveSelection	-4274.171771
Model 0: one-ratio	-4320.782785
Model 3: discrete	-4228.513401
Model 7: beta	-4235.071999
Model 8: beta&w>1	-4233.139613


Model 0 vs 1	93.22202800000014

Model 2 vs 1	0.0

Model 8 vs 7	3.864771999998993