--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Thu May 31 20:52:19 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_A1/NS2A_4/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_A1/NS2A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A1/NS2A_4/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_A1/NS2A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -7201.46         -7253.96
2      -7202.39         -7249.24
--------------------------------------
TOTAL    -7201.82         -7253.27
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_A1/NS2A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A1/NS2A_4/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_A1/NS2A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         9.820765    0.454806    8.520389   11.127270    9.804415    736.74    797.94    1.000
r(A<->C){all}   0.050193    0.000069    0.034819    0.066751    0.049850    884.19    899.18    1.000
r(A<->G){all}   0.215912    0.000299    0.182838    0.248851    0.215414    347.69    488.30    1.000
r(A<->T){all}   0.042210    0.000050    0.028883    0.055809    0.041963    913.25    921.23    1.000
r(C<->G){all}   0.040252    0.000068    0.024671    0.056529    0.039829    747.74    771.49    1.000
r(C<->T){all}   0.618243    0.000452    0.580485    0.663095    0.618340    370.34    465.53    1.001
r(G<->T){all}   0.033189    0.000053    0.019106    0.047645    0.032757    715.56    734.31    1.001
pi(A){all}      0.310305    0.000126    0.289432    0.332302    0.310077    924.90    938.17    1.000
pi(C){all}      0.207599    0.000084    0.190559    0.226494    0.207355    913.33    970.24    1.000
pi(G){all}      0.242157    0.000106    0.222212    0.262517    0.241862    746.67    850.18    1.000
pi(T){all}      0.239938    0.000108    0.220350    0.260696    0.239472    606.87    710.88    1.000
alpha{1,2}      0.409010    0.001651    0.335981    0.492150    0.405832   1205.20   1307.39    1.000
alpha{3}        4.415263    0.951286    2.657838    6.344344    4.308667   1385.98   1397.67    1.000
pinvar{all}     0.030466    0.000366    0.000017    0.065595    0.027642   1153.36   1292.62    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	-6982.606615
Model 2: PositiveSelection	-6982.606615
Model 0: one-ratio	-7008.284095
Model 3: discrete	-6923.090946
Model 7: beta	-6923.293679
Model 8: beta&w>1	-6923.294227


Model 0 vs 1	51.354960000000574

Model 2 vs 1	0.0

Model 8 vs 7	0.0010959999999613501