--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Fri Nov 18 01:42:48 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/105/CG30271-PF/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/105/CG30271-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/105/CG30271-PF/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/105/CG30271-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -2826.99         -2847.09
2      -2826.03         -2842.39
--------------------------------------
TOTAL    -2826.40         -2846.40
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/105/CG30271-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/105/CG30271-PF/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/105/CG30271-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         1.006019    0.009274    0.811624    1.189277    1.004319   1476.02   1488.51    1.000
r(A<->C){all}   0.092153    0.000337    0.058252    0.128712    0.091092    747.90    922.65    1.000
r(A<->G){all}   0.171612    0.000763    0.117693    0.224880    0.170491    950.21    980.21    1.000
r(A<->T){all}   0.081748    0.000654    0.036707    0.131569    0.079744    703.63    764.41    1.000
r(C<->G){all}   0.071254    0.000184    0.047356    0.099208    0.070426   1128.76   1201.33    1.000
r(C<->T){all}   0.488384    0.001558    0.416168    0.567437    0.487702    911.30    941.30    1.001
r(G<->T){all}   0.094849    0.000416    0.055688    0.134208    0.093584    937.17   1033.83    1.000
pi(A){all}      0.240563    0.000217    0.210593    0.268612    0.239931   1046.64   1090.30    1.001
pi(C){all}      0.290600    0.000209    0.263007    0.318780    0.290298   1040.86   1182.79    1.000
pi(G){all}      0.306362    0.000230    0.277052    0.336315    0.306136   1366.16   1408.92    1.001
pi(T){all}      0.162474    0.000132    0.139735    0.183871    0.162357    976.29   1075.19    1.000
alpha{1,2}      0.140327    0.000315    0.108565    0.175374    0.138831   1060.91   1237.79    1.000
alpha{3}        2.913458    0.694472    1.573391    4.715483    2.786817   1140.77   1213.26    1.000
pinvar{all}     0.422813    0.001944    0.330373    0.505072    0.423858   1324.85   1382.94    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	-2660.988257
Model 2: PositiveSelection	-2660.988257
Model 0: one-ratio	-2666.629381
Model 3: discrete	-2644.34978
Model 7: beta	-2645.430377
Model 8: beta&w>1	-2645.431403


Model 0 vs 1	11.282248000000436

Model 2 vs 1	0.0

Model 8 vs 7	0.002051999999821419