--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Thu Jun 07 20:01:12 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_A2/NS4B_3/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_A2/NS4B_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A2/NS4B_3/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_A2/NS4B_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -7742.29         -7788.73
2      -7741.85         -7784.54
--------------------------------------
TOTAL    -7742.04         -7788.06
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_A2/NS4B_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A2/NS4B_3/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_A2/NS4B_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         8.021583    0.219675    7.116084    8.947767    8.023963    917.04   1015.19    1.000
r(A<->C){all}   0.032591    0.000028    0.022289    0.043030    0.032328    572.86    758.11    1.000
r(A<->G){all}   0.240391    0.000341    0.206115    0.279873    0.240201    405.58    443.68    1.000
r(A<->T){all}   0.055773    0.000049    0.042826    0.069782    0.055303    814.31    901.33    1.000
r(C<->G){all}   0.021403    0.000032    0.010063    0.031876    0.021164    825.21    861.01    1.000
r(C<->T){all}   0.604692    0.000482    0.559999    0.647217    0.604738    433.18    456.09    1.000
r(G<->T){all}   0.045149    0.000058    0.029885    0.059436    0.044863    803.00    830.90    1.000
pi(A){all}      0.341047    0.000144    0.315999    0.362375    0.341513    862.15    864.67    1.000
pi(C){all}      0.237030    0.000106    0.217276    0.256439    0.236859    674.69    726.25    1.000
pi(G){all}      0.211900    0.000104    0.190293    0.230706    0.211654    663.87    692.94    1.000
pi(T){all}      0.210022    0.000090    0.190071    0.226591    0.209886    686.60    702.70    1.000
alpha{1,2}      0.220068    0.000205    0.192477    0.249390    0.219273   1060.11   1213.98    1.000
alpha{3}        5.719110    1.052021    3.861267    7.748860    5.616145   1152.32   1229.67    1.000
pinvar{all}     0.136102    0.000664    0.087277    0.187880    0.135159    819.56   1035.85    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 1: NearlyNeutral	-7296.264532
Model 2: PositiveSelection	-7296.264537
Model 0: one-ratio	-7314.39087
Model 3: discrete	-7217.962161
Model 7: beta	-7219.24212
Model 8: beta&w>1	-7219.24457


Model 0 vs 1	36.252676000000065

Model 2 vs 1	9.999999747378752E-6

Model 8 vs 7	0.004899999999906868