--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Fri Nov 25 13:23:56 WET 2016
codeml.models=0 1 2 3 7 8
mrbayes.mpich=
mrbayes.ngen=1000000
tcoffee.alignMethod=CLUSTALW2
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/ADOPS/1/14-3-3zeta-PB/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/1/14-3-3zeta-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PB/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/ADOPS/1/14-3-3zeta-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -1544.28         -1567.13
2      -1544.31         -1565.61
--------------------------------------
TOTAL    -1544.29         -1566.64
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/1/14-3-3zeta-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PB/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/ADOPS/1/14-3-3zeta-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         0.245856    0.001604    0.174180    0.325750    0.241814   1136.30   1318.65    1.000
r(A<->C){all}   0.113183    0.001243    0.049168    0.182604    0.109564    846.81    852.88    1.000
r(A<->G){all}   0.153348    0.001798    0.079640    0.240865    0.148999    811.48    856.54    1.000
r(A<->T){all}   0.066514    0.001006    0.012708    0.130478    0.062035    755.27    884.75    1.000
r(C<->G){all}   0.063165    0.000684    0.017561    0.114195    0.060155    884.58    960.25    1.001
r(C<->T){all}   0.553864    0.005036    0.409065    0.684867    0.555828    666.32    723.35    1.000
r(G<->T){all}   0.049926    0.000809    0.004077    0.103858    0.045310    858.11    927.24    1.000
pi(A){all}      0.285634    0.000263    0.254883    0.317959    0.285132   1182.12   1247.07    1.000
pi(C){all}      0.260975    0.000235    0.233004    0.293073    0.260752   1171.72   1183.73    1.000
pi(G){all}      0.258169    0.000240    0.227530    0.288645    0.258184   1228.06   1273.73    1.000
pi(T){all}      0.195222    0.000197    0.168133    0.222360    0.195008    961.99   1200.21    1.000
alpha{1,2}      0.056728    0.001797    0.000108    0.133540    0.048256   1004.00   1252.50    1.000
alpha{3}        2.093251    0.661590    0.714309    3.649766    1.970407   1230.32   1365.66    1.000
pinvar{all}     0.476075    0.008265    0.291909    0.633806    0.486202   1308.58   1341.06    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	-1451.36118
Model 2: PositiveSelection	-1451.36118
Model 0: one-ratio	-1458.92382
Model 3: discrete	-1451.332921
Model 7: beta	-1451.333746
Model 8: beta&w>1	-1451.361179


Model 0 vs 1	15.125279999999748

Model 2 vs 1	0.0

Model 8 vs 7	0.054865999999947235