--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Sun May 27 20:13:37 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_A1/NS1_5/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_A1/NS1_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A1/NS1_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_A1/NS1_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -8480.97         -8524.63
2      -8479.84         -8530.80
--------------------------------------
TOTAL    -8480.25         -8530.10
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_A1/NS1_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A1/NS1_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_A1/NS1_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}         6.942357    0.211954    6.078477    7.860914    6.920747    589.54    593.27    1.000
r(A<->C){all}   0.033506    0.000032    0.022772    0.044934    0.033260    672.35    735.94    1.000
r(A<->G){all}   0.224353    0.000289    0.192791    0.258018    0.224030    407.19    477.26    1.000
r(A<->T){all}   0.050758    0.000050    0.035939    0.063665    0.050396    715.10    757.96    1.000
r(C<->G){all}   0.024693    0.000041    0.012131    0.036706    0.024273    659.23    669.93    1.000
r(C<->T){all}   0.633661    0.000425    0.591217    0.671762    0.634703    470.58    490.66    1.000
r(G<->T){all}   0.033029    0.000056    0.017917    0.047016    0.032683    610.29    738.50    1.000
pi(A){all}      0.347461    0.000118    0.326581    0.367556    0.347314    758.33    840.36    1.000
pi(C){all}      0.226592    0.000078    0.209564    0.243641    0.226499    986.03   1011.28    1.000
pi(G){all}      0.225673    0.000086    0.208600    0.243877    0.225749    733.33    787.52    1.000
pi(T){all}      0.200274    0.000068    0.183005    0.215301    0.200245    877.85    925.69    1.000
alpha{1,2}      0.207268    0.000177    0.181243    0.233596    0.206991   1267.28   1269.20    1.000
alpha{3}        4.798278    0.834584    3.148953    6.619867    4.721129   1307.19   1368.48    1.000
pinvar{all}     0.138667    0.000557    0.093799    0.184496    0.138248   1095.76   1122.01    1.001
------------------------------------------------------------------------------------------------------
* 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	-8102.207801
Model 2: PositiveSelection	-8102.207801
Model 0: one-ratio	-8228.634391
Model 3: discrete	-8019.318829
Model 7: beta	-8024.756597
Model 8: beta&w>1	-8022.914789


Model 0 vs 1	252.85318000000007

Model 2 vs 1	0.0

Model 8 vs 7	3.6836159999984375