--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Thu Jul 12 02:13:48 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_N3/NS4B_1/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N3/NS4B_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/NS4B_1/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_N3/NS4B_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -5962.81         -6007.61
2      -5961.47         -6005.50
--------------------------------------
TOTAL    -5961.93         -6007.03
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N3/NS4B_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/NS4B_1/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_N3/NS4B_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         7.289096    0.234855    6.392444    8.228090    7.277219    887.52    908.19    1.000
r(A<->C){all}   0.044034    0.000059    0.029100    0.059385    0.043968    923.45    991.33    1.000
r(A<->G){all}   0.231089    0.000413    0.193975    0.272343    0.230222    523.92    537.84    1.001
r(A<->T){all}   0.057129    0.000080    0.040361    0.074667    0.056645    843.52    888.62    1.004
r(C<->G){all}   0.028866    0.000066    0.013203    0.044447    0.028441    673.83    773.88    1.000
r(C<->T){all}   0.614799    0.000607    0.567814    0.662558    0.615368    516.69    525.79    1.003
r(G<->T){all}   0.024084    0.000062    0.009297    0.039176    0.023592    785.81    806.63    1.001
pi(A){all}      0.337796    0.000148    0.315387    0.362197    0.337679    943.87    985.45    1.001
pi(C){all}      0.232480    0.000107    0.212495    0.252871    0.232382    802.77    911.41    1.001
pi(G){all}      0.217346    0.000113    0.195555    0.237754    0.217197    800.54    888.79    1.000
pi(T){all}      0.212378    0.000093    0.192874    0.230510    0.212287    835.04    898.33    1.001
alpha{1,2}      0.179789    0.000165    0.155748    0.204818    0.179078    902.08   1042.60    1.000
alpha{3}        4.313709    0.748055    2.719269    5.994901    4.203316   1416.71   1458.85    1.001
pinvar{all}     0.131891    0.000769    0.080795    0.186981    0.131564   1235.35   1243.18    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	-5408.319805
Model 2: PositiveSelection	-5408.319805
Model 0: one-ratio	-5421.441971
Model 3: discrete	-5346.019052
Model 7: beta	-5347.505404
Model 8: beta&w>1	-5347.507834


Model 0 vs 1	26.244332000000213

Model 2 vs 1	0.0

Model 8 vs 7	0.004859999999098363