--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Tue May 08 11:58:45 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_N2/NS2A_2/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N2/NS2A_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/NS2A_2/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_N2/NS2A_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -6358.13         -6405.70
2      -6356.96         -6403.10
--------------------------------------
TOTAL    -6357.38         -6405.08
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N2/NS2A_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/NS2A_2/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_N2/NS2A_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         9.548085    0.487475    8.176708   10.891300    9.529109    510.16    617.49    1.000
r(A<->C){all}   0.047911    0.000078    0.031588    0.066215    0.047409    731.62    832.54    1.000
r(A<->G){all}   0.215643    0.000345    0.181863    0.253837    0.215102    600.78    629.96    1.000
r(A<->T){all}   0.047195    0.000076    0.030392    0.064492    0.046880    696.77    822.24    1.001
r(C<->G){all}   0.040415    0.000100    0.021995    0.060317    0.039880    579.31    649.57    1.000
r(C<->T){all}   0.612638    0.000514    0.567190    0.657025    0.612702    554.85    646.32    1.000
r(G<->T){all}   0.036197    0.000081    0.018982    0.053569    0.035502    663.78    794.12    1.000
pi(A){all}      0.312225    0.000132    0.291281    0.335848    0.311960    904.87    918.64    1.000
pi(C){all}      0.210386    0.000093    0.192708    0.230710    0.210216    639.22    650.35    1.000
pi(G){all}      0.241728    0.000114    0.220169    0.261711    0.241632    569.35    638.73    1.000
pi(T){all}      0.235660    0.000106    0.214447    0.254498    0.235511    666.22    814.09    1.000
alpha{1,2}      0.387883    0.001552    0.313329    0.461967    0.384381   1091.64   1159.01    1.000
alpha{3}        3.641500    0.703365    2.120942    5.294857    3.543628   1292.23   1394.14    1.000
pinvar{all}     0.023798    0.000306    0.000001    0.057398    0.020292   1102.29   1139.68    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	-5914.519222
Model 2: PositiveSelection	-5914.519222
Model 0: one-ratio	-5933.104667
Model 3: discrete	-5860.306763
Model 7: beta	-5862.582064
Model 8: beta&w>1	-5862.582312


Model 0 vs 1	37.17088999999942

Model 2 vs 1	0.0

Model 8 vs 7	4.959999987477204E-4