--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Fri Jul 13 07:50:48 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/NS4B_3/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N3/NS4B_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/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_N3/NS4B_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -6062.49         -6104.88
2      -6064.49         -6105.84
--------------------------------------
TOTAL    -6063.06         -6105.47
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N3/NS4B_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/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_N3/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}         7.311652    0.244854    6.406078    8.344652    7.300631    756.58    830.02    1.000
r(A<->C){all}   0.038433    0.000049    0.025029    0.051937    0.038178    723.43    871.60    1.000
r(A<->G){all}   0.220040    0.000389    0.183060    0.260135    0.219264    559.12    593.49    1.000
r(A<->T){all}   0.049728    0.000062    0.035067    0.065270    0.049220    796.34    908.41    1.001
r(C<->G){all}   0.028186    0.000060    0.013783    0.043451    0.027653    746.12    759.84    1.000
r(C<->T){all}   0.635106    0.000559    0.592684    0.684394    0.635664    572.51    647.25    1.000
r(G<->T){all}   0.028507    0.000060    0.014180    0.043607    0.028017    728.61    798.72    1.000
pi(A){all}      0.335847    0.000153    0.312087    0.360493    0.335754    727.59    807.00    1.000
pi(C){all}      0.230527    0.000099    0.212034    0.251292    0.230376    837.48    902.30    1.000
pi(G){all}      0.212170    0.000107    0.192292    0.232509    0.212122    810.04   1005.14    1.000
pi(T){all}      0.221455    0.000108    0.200791    0.241913    0.221056    814.97    825.18    1.000
alpha{1,2}      0.182573    0.000165    0.157226    0.206168    0.181750    965.08   1112.92    1.000
alpha{3}        4.927679    0.978321    3.109605    6.881684    4.828890   1479.54   1490.27    1.000
pinvar{all}     0.138518    0.000846    0.081783    0.195865    0.137491   1370.13   1390.18    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	-5568.971649
Model 2: PositiveSelection	-5568.971649
Model 0: one-ratio	-5591.609224
Model 3: discrete	-5504.151449
Model 7: beta	-5505.475438
Model 8: beta&w>1	-5504.225466


Model 0 vs 1	45.275149999999485

Model 2 vs 1	0.0

Model 8 vs 7	2.499944000001051