--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Sat May 05 01:01:32 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_2/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N1/NS1_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N1/NS1_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/ADOPS1/DNG_N1/NS1_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -8960.72         -9009.30
2      -8961.78         -9005.03
--------------------------------------
TOTAL    -8961.12         -9008.62
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N1/NS1_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N1/NS1_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/ADOPS1/DNG_N1/NS1_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}         7.792185    0.242197    6.835030    8.748124    7.762955    654.84    673.73    1.001
r(A<->C){all}   0.028577    0.000026    0.019043    0.038783    0.028395    843.15    871.76    1.002
r(A<->G){all}   0.220253    0.000252    0.189133    0.250636    0.220001    519.42    590.57    1.005
r(A<->T){all}   0.055693    0.000047    0.042811    0.069122    0.055311    889.61    894.53    1.000
r(C<->G){all}   0.023263    0.000032    0.013112    0.034483    0.022897    775.46    831.79    1.000
r(C<->T){all}   0.653654    0.000349    0.619141    0.690421    0.653577    561.56    585.36    1.007
r(G<->T){all}   0.018559    0.000036    0.007671    0.031189    0.018216    630.06    766.25    1.000
pi(A){all}      0.344289    0.000107    0.325413    0.365957    0.344333    800.27    880.45    1.001
pi(C){all}      0.231198    0.000075    0.214244    0.248421    0.231148    504.15    741.29    1.003
pi(G){all}      0.230409    0.000083    0.212691    0.247952    0.230384    845.47    853.79    1.000
pi(T){all}      0.194104    0.000061    0.179200    0.209735    0.194227    845.09    964.00    1.000
alpha{1,2}      0.193714    0.000138    0.170727    0.216343    0.193170   1230.80   1242.77    1.000
alpha{3}        5.803558    1.152172    3.896037    7.963801    5.661483   1501.00   1501.00    1.000
pinvar{all}     0.135554    0.000507    0.093593    0.180917    0.134787    987.77   1152.01    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	-8598.078479
Model 2: PositiveSelection	-8598.078479
Model 0: one-ratio	-8702.716886
Model 3: discrete	-8491.209645
Model 7: beta	-8494.419795
Model 8: beta&w>1	-8492.756939


Model 0 vs 1	209.27681400000074

Model 2 vs 1	0.0

Model 8 vs 7	3.3257119999980205