--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Wed Dec 20 02:57:21 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_4/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DGA_B3/NS5_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_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/ADOPS/DGA_B3/NS5_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -22261.63        -22306.60
2     -22260.87        -22309.05
--------------------------------------
TOTAL   -22261.18        -22308.44
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DGA_B3/NS5_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_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/ADOPS/DGA_B3/NS5_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}         6.901823    0.105917    6.310940    7.577892    6.891951    289.93    479.11    1.001
r(A<->C){all}   0.036078    0.000011    0.029510    0.042357    0.035941    639.43    741.41    1.000
r(A<->G){all}   0.187926    0.000084    0.170803    0.205794    0.187432    481.29    548.73    1.001
r(A<->T){all}   0.049003    0.000017    0.041178    0.057169    0.049005    776.80    823.43    1.000
r(C<->G){all}   0.023166    0.000012    0.016130    0.029761    0.023030    809.36    858.00    1.001
r(C<->T){all}   0.674360    0.000143    0.651804    0.698135    0.674677    444.27    486.46    1.000
r(G<->T){all}   0.029466    0.000018    0.021531    0.037837    0.029239    539.00    696.26    1.000
pi(A){all}      0.361198    0.000046    0.347720    0.374376    0.361209    655.80    674.76    1.000
pi(C){all}      0.221810    0.000031    0.211592    0.233131    0.221724    589.21    719.72    1.001
pi(G){all}      0.236345    0.000037    0.225214    0.248683    0.236320    603.10    706.81    1.000
pi(T){all}      0.180646    0.000023    0.171572    0.190194    0.180616    721.33    766.58    1.000
alpha{1,2}      0.197757    0.000065    0.181236    0.212643    0.197520   1260.71   1301.89    1.000
alpha{3}        5.738891    0.740447    4.143632    7.400518    5.668143    923.80   1184.75    1.000
pinvar{all}     0.126623    0.000209    0.099024    0.154283    0.126642    959.77   1028.67    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, 	-21597.040755