--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Wed May 30 22:48:27 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_2/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_A1/NS2A_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A1/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_A1/NS2A_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -8385.58 -8434.60
2 -8382.77 -8441.80
--------------------------------------
TOTAL -8383.40 -8441.11
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_A1/NS2A_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A1/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_A1/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} 11.566017 0.534391 10.104130 12.923390 11.532040 671.81 708.33 1.000
r(A<->C){all} 0.049471 0.000059 0.035362 0.064765 0.049294 796.87 855.08 1.000
r(A<->G){all} 0.226667 0.000276 0.193948 0.258717 0.226234 532.12 544.99 1.000
r(A<->T){all} 0.045942 0.000043 0.033464 0.058841 0.045826 747.90 882.39 1.001
r(C<->G){all} 0.044026 0.000062 0.029417 0.059468 0.043731 948.69 982.74 1.002
r(C<->T){all} 0.595115 0.000410 0.556346 0.634547 0.595283 535.27 545.81 1.000
r(G<->T){all} 0.038779 0.000053 0.024843 0.052531 0.038489 845.10 858.86 1.000
pi(A){all} 0.317967 0.000120 0.297092 0.339066 0.317420 719.26 750.03 1.000
pi(C){all} 0.209727 0.000079 0.191770 0.225931 0.209913 889.76 897.60 1.000
pi(G){all} 0.239231 0.000091 0.221292 0.258406 0.238885 874.71 907.46 1.000
pi(T){all} 0.233075 0.000089 0.214937 0.251503 0.233252 709.88 826.80 1.000
alpha{1,2} 0.416498 0.001904 0.336330 0.506916 0.413370 1130.99 1133.15 1.000
alpha{3} 4.915084 1.056482 3.055367 6.934221 4.797835 1394.75 1396.74 1.000
pinvar{all} 0.056982 0.000505 0.014197 0.099763 0.055434 1024.21 1072.58 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 -8068.479572
Model 2: PositiveSelection -8068.479572
Model 0: one-ratio -8099.531773
Model 3: discrete -8002.302433
Model 7: beta -8005.758876
Model 8: beta&w>1 -8005.761042
Model 0 vs 1 62.10440199999903
Model 2 vs 1 0.0
Model 8 vs 7 0.004332000000431435
