--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Sun Jul 15 16:39:02 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_N3/prM_4/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N3/prM_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/prM_4/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_N3/prM_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -4194.45         -4234.85
2      -4190.64         -4240.11
--------------------------------------
TOTAL    -4191.31         -4239.42
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N3/prM_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/prM_4/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_N3/prM_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         6.997234    0.283086    5.958965    8.023488    6.983296    643.34    942.66    1.000
r(A<->C){all}   0.040342    0.000074    0.024139    0.057363    0.039951    906.65    955.27    1.000
r(A<->G){all}   0.189127    0.000497    0.145193    0.229938    0.189010    543.26    647.83    1.000
r(A<->T){all}   0.060547    0.000121    0.038913    0.081604    0.060061    950.94    961.27    1.000
r(C<->G){all}   0.022341    0.000056    0.008633    0.036798    0.021847    792.87    904.59    1.001
r(C<->T){all}   0.651113    0.000797    0.596612    0.706436    0.651107    477.95    648.26    1.000
r(G<->T){all}   0.036531    0.000101    0.018678    0.056452    0.035896    790.10    830.00    1.001
pi(A){all}      0.300643    0.000217    0.272338    0.328294    0.300586    912.73    976.66    1.000
pi(C){all}      0.250444    0.000180    0.225358    0.278139    0.250259    762.65    763.96    1.000
pi(G){all}      0.239497    0.000216    0.210454    0.266969    0.239141    821.35    835.78    1.000
pi(T){all}      0.209416    0.000140    0.186480    0.233125    0.209175    862.16    941.38    1.000
alpha{1,2}      0.196338    0.000267    0.164671    0.228289    0.195265   1149.25   1242.09    1.000
alpha{3}        3.724688    0.688380    2.257511    5.427526    3.624487   1402.51   1451.76    1.000
pinvar{all}     0.047002    0.000788    0.000020    0.097018    0.044753   1410.60   1455.80    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	-3953.082254
Model 2: PositiveSelection	-3953.082254
Model 0: one-ratio	-3966.810545
Model 3: discrete	-3919.447424
Model 7: beta	-3921.588518
Model 8: beta&w>1	-3921.589525


Model 0 vs 1	27.4565819999998

Model 2 vs 1	0.0

Model 8 vs 7	0.002013999999689986