--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Sat Oct 07 11:55:40 WEST 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=/usr/bin/
input.sequences=
mrbayes.pburnin=2500
mrbayes.bin=mb
tcoffee.bin=t_coffee
mrbayes.dir=/usr/bin/
tcoffee.dir=
tcoffee.minScore=3
input.fasta=/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_3/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_3/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/ADOPS/DATA/Zika/B2_A/Zika-NS1_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -4124.84         -4206.67
2      -4141.24         -4211.12
--------------------------------------
TOTAL    -4125.53         -4210.44
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_3/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/ADOPS/DATA/Zika/B2_A/Zika-NS1_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}        16.912742    2.151838   13.946200   19.710080   16.876350    711.01    755.22    1.000
r(A<->C){all}   0.026113    0.000058    0.012480    0.040609    0.025414    578.87    622.49    1.001
r(A<->G){all}   0.241520    0.001029    0.183967    0.310206    0.240246    388.38    399.46    1.002
r(A<->T){all}   0.031994    0.000078    0.014953    0.048542    0.031066    510.59    661.83    1.002
r(C<->G){all}   0.016535    0.000041    0.005562    0.029630    0.015891    725.12    763.36    1.001
r(C<->T){all}   0.664716    0.001273    0.592778    0.732181    0.665640    368.91    381.01    1.000
r(G<->T){all}   0.019123    0.000049    0.006420    0.032900    0.018211    548.02    650.33    1.000
pi(A){all}      0.284204    0.000165    0.257874    0.308473    0.284109    819.80    879.85    1.001
pi(C){all}      0.209433    0.000121    0.187924    0.231386    0.209232    592.28    770.67    1.000
pi(G){all}      0.301573    0.000175    0.273809    0.326595    0.301572    586.85    714.07    1.003
pi(T){all}      0.204789    0.000119    0.183758    0.226283    0.204479    722.98    772.40    1.000
alpha{1,2}      0.069356    0.000008    0.063477    0.074324    0.069329    726.99    777.30    1.000
alpha{3}        0.240504    0.000139    0.218371    0.263493    0.239606    645.28    689.71    1.000
pinvar{all}     0.443283    0.001016    0.380726    0.504553    0.444082    838.87    931.87    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	-3348.764702
Model 2: PositiveSelection	-3348.764702
Model 0: one-ratio	-3362.117927
Model 3: discrete	-3343.552193
Model 7: beta	-3343.93651
Model 8: beta&w>1	-3343.939139


Model 0 vs 1	26.706449999999677

Model 2 vs 1	0.0

Model 8 vs 7	0.005258000000139873