--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Thu May 31 20:52:19 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/NS2A_4/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_A1/NS2A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A1/NS2A_4/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/NS2A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -7201.46 -7253.96
2 -7202.39 -7249.24
--------------------------------------
TOTAL -7201.82 -7253.27
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_A1/NS2A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A1/NS2A_4/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/NS2A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 9.820765 0.454806 8.520389 11.127270 9.804415 736.74 797.94 1.000
r(A<->C){all} 0.050193 0.000069 0.034819 0.066751 0.049850 884.19 899.18 1.000
r(A<->G){all} 0.215912 0.000299 0.182838 0.248851 0.215414 347.69 488.30 1.000
r(A<->T){all} 0.042210 0.000050 0.028883 0.055809 0.041963 913.25 921.23 1.000
r(C<->G){all} 0.040252 0.000068 0.024671 0.056529 0.039829 747.74 771.49 1.000
r(C<->T){all} 0.618243 0.000452 0.580485 0.663095 0.618340 370.34 465.53 1.001
r(G<->T){all} 0.033189 0.000053 0.019106 0.047645 0.032757 715.56 734.31 1.001
pi(A){all} 0.310305 0.000126 0.289432 0.332302 0.310077 924.90 938.17 1.000
pi(C){all} 0.207599 0.000084 0.190559 0.226494 0.207355 913.33 970.24 1.000
pi(G){all} 0.242157 0.000106 0.222212 0.262517 0.241862 746.67 850.18 1.000
pi(T){all} 0.239938 0.000108 0.220350 0.260696 0.239472 606.87 710.88 1.000
alpha{1,2} 0.409010 0.001651 0.335981 0.492150 0.405832 1205.20 1307.39 1.000
alpha{3} 4.415263 0.951286 2.657838 6.344344 4.308667 1385.98 1397.67 1.000
pinvar{all} 0.030466 0.000366 0.000017 0.065595 0.027642 1153.36 1292.62 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 -6982.606615
Model 2: PositiveSelection -6982.606615
Model 0: one-ratio -7008.284095
Model 3: discrete -6923.090946
Model 7: beta -6923.293679
Model 8: beta&w>1 -6923.294227
Model 0 vs 1 51.354960000000574
Model 2 vs 1 0.0
Model 8 vs 7 0.0010959999999613501
