--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Fri May 04 08:39:17 WEST 2018
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=
input.sequences=
mrbayes.pburnin=2500
mrbayes.bin=mb_adops
tcoffee.bin=t_coffee_ADOPS
mrbayes.dir=/usr/bin/
tcoffee.dir=
tcoffee.minScore=3
input.fasta=/opt/ADOPS1/DNG_N1/NS1_1/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N1/NS1_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N1/NS1_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/ADOPS1/DNG_N1/NS1_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -8288.60         -8339.00
2      -8289.73         -8335.05
--------------------------------------
TOTAL    -8289.01         -8338.33
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N1/NS1_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N1/NS1_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/ADOPS1/DNG_N1/NS1_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}         7.629462    0.264793    6.664328    8.648123    7.615478    626.90    630.16    1.000
r(A<->C){all}   0.027256    0.000031    0.016680    0.038603    0.027068    915.24    920.38    1.000
r(A<->G){all}   0.214614    0.000290    0.180679    0.246830    0.214410    431.54    540.16    1.000
r(A<->T){all}   0.054603    0.000054    0.040500    0.069083    0.054372    677.09    782.05    1.000
r(C<->G){all}   0.026701    0.000044    0.014042    0.039669    0.026263    542.31    740.79    1.000
r(C<->T){all}   0.657788    0.000427    0.619472    0.700583    0.657409    402.98    504.74    1.000
r(G<->T){all}   0.019037    0.000043    0.006703    0.031868    0.018747    750.48    751.18    1.000
pi(A){all}      0.347989    0.000109    0.328535    0.369582    0.347952    678.08    788.42    1.001
pi(C){all}      0.230371    0.000083    0.213430    0.248975    0.230040    938.95   1006.28    1.001
pi(G){all}      0.224151    0.000089    0.207534    0.243785    0.223809    672.00    819.42    1.000
pi(T){all}      0.197489    0.000063    0.182538    0.213198    0.197507    464.53    617.41    1.000
alpha{1,2}      0.194319    0.000141    0.172632    0.218273    0.193720   1146.54   1259.02    1.000
alpha{3}        4.908844    0.902357    3.132158    6.668747    4.812321   1128.50   1314.75    1.000
pinvar{all}     0.142613    0.000575    0.097070    0.187134    0.141572    923.34   1029.30    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	-7921.44414
Model 2: PositiveSelection	-7921.44414
Model 0: one-ratio	-8031.533019
Model 3: discrete	-7827.202985
Model 7: beta	-7831.309872
Model 8: beta&w>1	-7829.697256


Model 0 vs 1	220.17775800000163

Model 2 vs 1	0.0

Model 8 vs 7	3.2252319999988686