--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Thu May 03 12:37:24 WEST 2018
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/DNGB3/NS5_1/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DNGB3/NS5_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DNGB3/NS5_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/ADOPS/DNGB3/NS5_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -20367.91        -20409.11
2     -20369.96        -20418.84
--------------------------------------
TOTAL   -20368.48        -20418.14
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DNGB3/NS5_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DNGB3/NS5_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/ADOPS/DNGB3/NS5_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}         6.947938    0.119275    6.270727    7.621546    6.940277    443.53    450.31    1.003
r(A<->C){all}   0.041561    0.000014    0.034482    0.048514    0.041486    752.87    814.19    1.000
r(A<->G){all}   0.185576    0.000099    0.167504    0.205517    0.185120    362.56    375.03    1.001
r(A<->T){all}   0.044012    0.000020    0.035257    0.052654    0.043892    607.12    756.36    1.004
r(C<->G){all}   0.024335    0.000014    0.017733    0.032285    0.024186    593.53    699.99    1.000
r(C<->T){all}   0.682253    0.000166    0.656038    0.706038    0.682698    356.06    374.44    1.000
r(G<->T){all}   0.022264    0.000017    0.014851    0.030837    0.022049    647.41    718.30    1.000
pi(A){all}      0.359896    0.000043    0.346897    0.372397    0.360104    730.19    751.51    1.000
pi(C){all}      0.224134    0.000031    0.212589    0.234313    0.224091    725.38    738.22    1.000
pi(G){all}      0.235686    0.000037    0.223808    0.247254    0.235537    772.16    777.42    1.002
pi(T){all}      0.180285    0.000023    0.170948    0.189773    0.180151    508.11    612.78    1.000
alpha{1,2}      0.188527    0.000061    0.172768    0.203394    0.188374   1005.07   1007.69    1.000
alpha{3}        6.044479    0.932346    4.170510    7.889688    5.961256   1501.00   1501.00    1.000
pinvar{all}     0.145187    0.000231    0.116380    0.174606    0.144524   1143.53   1183.29    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, 	-19422.972821