--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Fri Nov 25 13:46:46 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-PD/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

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

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -1343.20         -1378.56
2      -1341.42         -1380.48
--------------------------------------
TOTAL    -1341.96         -1379.93
--------------------------------------


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

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         0.477927    0.065319    0.141454    0.988819    0.412012    948.75   1008.96    1.000
r(A<->C){all}   0.069693    0.001475    0.003106    0.143031    0.063784    455.10    516.27    1.001
r(A<->G){all}   0.243666    0.017767    0.036892    0.510775    0.216142    170.62    220.06    1.011
r(A<->T){all}   0.065585    0.001437    0.002272    0.137898    0.059483    520.54    563.23    1.002
r(C<->G){all}   0.044733    0.000823    0.000657    0.101570    0.038560    439.97    605.20    1.001
r(C<->T){all}   0.559002    0.023770    0.273571    0.851358    0.568327    188.96    205.75    1.010
r(G<->T){all}   0.017320    0.000319    0.000043    0.051130    0.011605    763.09    866.70    1.000
pi(A){all}      0.279750    0.000269    0.247980    0.312542    0.279585   1054.58   1165.22    1.000
pi(C){all}      0.259495    0.000250    0.228881    0.289029    0.258881   1076.65   1234.12    1.000
pi(G){all}      0.260475    0.000243    0.229630    0.290096    0.259990    926.83   1047.63    1.000
pi(T){all}      0.200279    0.000205    0.171491    0.227611    0.200212   1054.52   1160.42    1.000
alpha{1,2}      0.092865    0.000793    0.033581    0.158529    0.091075    928.29   1007.01    1.000
alpha{3}        1.211923    0.406711    0.258565    2.457056    1.083655   1042.64   1079.11    1.000
pinvar{all}     0.825988    0.001185    0.757798    0.887158    0.830301   1061.04   1078.22    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	-1263.066771
Model 2: PositiveSelection	-1263.066771
Model 0: one-ratio	-1264.026193
Model 3: discrete	-1263.063085
Model 7: beta	-1263.3924
Model 8: beta&w>1	-1263.066768


Model 0 vs 1	1.9188439999998081

Model 2 vs 1	0.0

Model 8 vs 7	0.6512640000000829