--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Wed Dec 20 00:16:15 WET 2017
codeml.models=
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/DGA_B3/NS5_3/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DGA_B3/NS5_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_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/DGA_B3/NS5_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -22634.19        -22683.08
2     -22632.55        -22672.67
--------------------------------------
TOTAL   -22633.07        -22682.38
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DGA_B3/NS5_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_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/DGA_B3/NS5_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}         7.037542    0.097834    6.395721    7.609735    7.030455    578.24    617.18    1.000
r(A<->C){all}   0.042441    0.000013    0.035781    0.049905    0.042350    773.35    784.55    1.000
r(A<->G){all}   0.186218    0.000087    0.169674    0.206261    0.186328    417.78    462.68    1.000
r(A<->T){all}   0.044348    0.000017    0.036675    0.052578    0.044256    833.11    867.77    1.003
r(C<->G){all}   0.025629    0.000013    0.018868    0.032974    0.025496    649.03    708.10    1.000
r(C<->T){all}   0.672155    0.000152    0.648429    0.695746    0.672036    320.23    409.76    1.000
r(G<->T){all}   0.029208    0.000018    0.021337    0.037763    0.029085    604.95    645.87    1.001
pi(A){all}      0.357967    0.000044    0.345457    0.371441    0.358113    760.35    864.55    1.001
pi(C){all}      0.222637    0.000030    0.211813    0.233332    0.222653    784.96    814.45    1.000
pi(G){all}      0.239866    0.000036    0.227339    0.250895    0.239847    537.16    597.14    1.000
pi(T){all}      0.179530    0.000022    0.170567    0.189439    0.179510    579.89    703.03    1.000
alpha{1,2}      0.200829    0.000065    0.185507    0.216860    0.200509   1342.45   1421.72    1.000
alpha{3}        6.169726    0.826998    4.494364    7.974510    6.056387   1125.57   1313.29    1.000
pinvar{all}     0.129875    0.000211    0.102624    0.159955    0.129611   1315.55   1320.75    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: One dN/dS ratio for branches, 	-21894.990207