--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Tue Nov 22 03:35:29 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/3/Acon-PB/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

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

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -7998.01         -8017.48
2      -7998.47         -8015.01
--------------------------------------
TOTAL    -7998.21         -8016.87
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/3/Acon-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/3/Acon-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/3/Acon-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}         0.996975    0.002714    0.901702    1.103123    0.994862   1168.44   1264.58    1.000
r(A<->C){all}   0.063677    0.000087    0.046344    0.082682    0.063289    996.95   1050.39    1.000
r(A<->G){all}   0.161645    0.000305    0.129517    0.197089    0.161357    944.25    964.01    1.000
r(A<->T){all}   0.106416    0.000301    0.071551    0.138749    0.106220    983.07   1041.18    1.001
r(C<->G){all}   0.050163    0.000044    0.037705    0.063625    0.049976   1152.00   1188.53    1.000
r(C<->T){all}   0.534763    0.000601    0.491987    0.585625    0.534856    713.77    795.37    1.000
r(G<->T){all}   0.083336    0.000124    0.061320    0.104595    0.082856   1215.74   1310.32    1.000
pi(A){all}      0.215627    0.000070    0.199796    0.232044    0.215598   1137.34   1144.67    1.000
pi(C){all}      0.324476    0.000079    0.306776    0.341259    0.324297    940.62   1063.18    1.000
pi(G){all}      0.272241    0.000077    0.256423    0.290243    0.272165   1142.70   1149.75    1.000
pi(T){all}      0.187656    0.000051    0.174913    0.202724    0.187545   1062.55   1134.29    1.000
alpha{1,2}      0.105143    0.000057    0.090836    0.120260    0.104921   1320.73   1406.14    1.000
alpha{3}        5.212324    1.260173    3.287058    7.506998    5.061816   1233.10   1367.05    1.000
pinvar{all}     0.346586    0.000700    0.292826    0.395863    0.347289   1130.66   1315.83    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	-7488.36443
Model 2: PositiveSelection	-7488.36443
Model 0: one-ratio	-7561.165264
Model 3: discrete	-7461.165259
Model 7: beta	-7461.607272
Model 8: beta&w>1	-7461.60783


Model 0 vs 1	145.60166800000115

Model 2 vs 1	0.0

Model 8 vs 7	0.0011159999994561076