--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Sat Jun 16 11:12:55 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_A2/prM_5/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_A2/prM_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A2/prM_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_A2/prM_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -4434.04 -4481.02
2 -4430.78 -4477.94
--------------------------------------
TOTAL -4431.44 -4480.37
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_A2/prM_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A2/prM_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_A2/prM_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} 6.260804 0.204678 5.380550 7.143599 6.260414 950.79 996.33 1.000
r(A<->C){all} 0.046927 0.000076 0.032047 0.065087 0.046291 606.09 758.47 1.000
r(A<->G){all} 0.190561 0.000483 0.151254 0.235823 0.189495 606.07 615.91 1.000
r(A<->T){all} 0.048055 0.000089 0.030364 0.067317 0.047710 785.90 892.30 1.001
r(C<->G){all} 0.028361 0.000059 0.013864 0.043423 0.027956 653.47 768.80 1.000
r(C<->T){all} 0.646253 0.000807 0.587387 0.695705 0.647031 594.96 604.15 1.000
r(G<->T){all} 0.039844 0.000097 0.020580 0.057904 0.039235 691.98 812.72 1.000
pi(A){all} 0.299448 0.000217 0.268872 0.326821 0.299310 913.72 950.96 1.000
pi(C){all} 0.250514 0.000176 0.224815 0.275948 0.250458 847.17 901.01 1.000
pi(G){all} 0.244273 0.000198 0.216975 0.271861 0.243965 652.61 789.45 1.000
pi(T){all} 0.205765 0.000143 0.182493 0.229103 0.205519 842.48 867.04 1.000
alpha{1,2} 0.223745 0.000396 0.185657 0.262563 0.222406 1149.65 1202.88 1.000
alpha{3} 3.933662 0.785960 2.368686 5.699515 3.815768 1372.77 1404.03 1.000
pinvar{all} 0.047295 0.000818 0.000165 0.098383 0.044923 986.51 1173.32 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 -4274.171771
Model 2: PositiveSelection -4274.171771
Model 0: one-ratio -4320.782785
Model 3: discrete -4228.513401
Model 7: beta -4235.071999
Model 8: beta&w>1 -4233.139613
Model 0 vs 1 93.22202800000014
Model 2 vs 1 0.0
Model 8 vs 7 3.864771999998993
