--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Tue Dec 19 21:39:09 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_2/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DGA_B3/NS5_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_2/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_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -22759.85        -22800.75
2     -22760.11        -22803.18
--------------------------------------
TOTAL   -22759.97        -22802.57
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DGA_B3/NS5_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_2/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_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         7.721383    0.115024    7.030942    8.348635    7.706858    365.90    498.67    1.000
r(A<->C){all}   0.038344    0.000011    0.031640    0.045020    0.038193    662.36    750.03    1.000
r(A<->G){all}   0.206044    0.000101    0.187766    0.225843    0.205760    368.94    389.23    1.000
r(A<->T){all}   0.046190    0.000017    0.038407    0.054461    0.046089    719.86    884.01    1.000
r(C<->G){all}   0.021441    0.000012    0.015036    0.028345    0.021337    507.14    643.29    1.000
r(C<->T){all}   0.660431    0.000158    0.637136    0.685327    0.660542    346.38    385.30    1.000
r(G<->T){all}   0.027549    0.000017    0.019478    0.035397    0.027471    676.66    774.06    1.001
pi(A){all}      0.363059    0.000040    0.350143    0.374927    0.363172    560.39    658.09    1.002
pi(C){all}      0.223394    0.000028    0.213462    0.234309    0.223388    583.99    673.56    1.002
pi(G){all}      0.235058    0.000032    0.224303    0.246688    0.234999    601.16    702.97    1.000
pi(T){all}      0.178490    0.000021    0.169861    0.187944    0.178437    586.84    612.71    1.000
alpha{1,2}      0.187743    0.000057    0.172751    0.202393    0.187514   1030.88   1097.28    1.001
alpha{3}        6.037151    0.828804    4.452672    7.948138    5.935705   1294.61   1397.80    1.000
pinvar{all}     0.138376    0.000207    0.109769    0.166592    0.138274   1108.20   1134.43    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: One dN/dS ratio for branches, 	-22004.768339