--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Thu May 03 15:07:15 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_N1/E_5/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N1/E_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N1/E_5/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_N1/E_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -12239.74        -12286.21
2     -12238.53        -12291.36
--------------------------------------
TOTAL   -12238.96        -12290.67
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N1/E_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N1/E_5/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_N1/E_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         8.945854    0.287377    7.991090   10.034280    8.917087    515.01    651.12    1.000
r(A<->C){all}   0.041307    0.000027    0.030601    0.050829    0.041020    612.15    692.28    1.000
r(A<->G){all}   0.182715    0.000146    0.159813    0.205367    0.182464    320.64    508.08    1.001
r(A<->T){all}   0.050040    0.000035    0.038216    0.061534    0.049986    473.69    686.10    1.000
r(C<->G){all}   0.015137    0.000016    0.007830    0.023260    0.014929    969.73    971.29    1.006
r(C<->T){all}   0.681954    0.000243    0.653149    0.712402    0.682130    237.91    464.81    1.002
r(G<->T){all}   0.028848    0.000029    0.018325    0.039302    0.028618    563.16    731.43    1.000
pi(A){all}      0.347795    0.000072    0.332011    0.365015    0.347649    619.81    726.76    1.001
pi(C){all}      0.219274    0.000051    0.204842    0.233093    0.219387    735.50    777.57    1.000
pi(G){all}      0.240934    0.000058    0.225859    0.254923    0.240957    814.69    876.80    1.000
pi(T){all}      0.191997    0.000044    0.178945    0.204599    0.191875    500.92    709.56    1.000
alpha{1,2}      0.203233    0.000118    0.181688    0.223570    0.202619    994.21   1122.13    1.000
alpha{3}        4.540831    0.600213    3.153307    6.128505    4.454810   1209.16   1355.08    1.000
pinvar{all}     0.099068    0.000342    0.064354    0.136244    0.097965   1180.10   1214.44    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	-11431.863105
Model 2: PositiveSelection	-11431.863109
Model 0: one-ratio	-11466.23619
Model 3: discrete	-11281.208712
Model 7: beta	-11283.169663
Model 8: beta&w>1	-11283.172841


Model 0 vs 1	68.74616999999853

Model 2 vs 1	7.99999907030724E-6

Model 8 vs 7	0.0063559999980498105