--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Thu May 17 00:08:26 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/NS3_4/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N2/NS3_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/NS3_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_N2/NS3_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -14770.56 -14813.13
2 -14775.50 -14813.15
--------------------------------------
TOTAL -14771.25 -14813.14
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N2/NS3_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/NS3_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_N2/NS3_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} 8.185872 0.189091 7.347523 9.071210 8.177417 664.08 668.67 1.002
r(A<->C){all} 0.034804 0.000017 0.026693 0.042846 0.034609 764.15 765.21 1.001
r(A<->G){all} 0.209424 0.000142 0.186555 0.233039 0.208763 490.19 496.38 1.000
r(A<->T){all} 0.038119 0.000019 0.029949 0.046667 0.038002 505.75 615.27 1.000
r(C<->G){all} 0.020329 0.000016 0.013235 0.028750 0.020111 865.41 1010.98 1.001
r(C<->T){all} 0.673086 0.000215 0.644184 0.700414 0.673078 466.53 491.78 1.000
r(G<->T){all} 0.024238 0.000020 0.015736 0.032874 0.024139 598.34 752.62 1.000
pi(A){all} 0.359847 0.000065 0.345068 0.376935 0.359777 806.67 873.95 1.000
pi(C){all} 0.217959 0.000041 0.206173 0.230629 0.217880 666.69 769.62 1.000
pi(G){all} 0.225849 0.000047 0.212260 0.239272 0.225878 758.21 773.07 1.002
pi(T){all} 0.196344 0.000035 0.184556 0.207669 0.196175 756.06 802.74 1.001
alpha{1,2} 0.158008 0.000048 0.145132 0.171703 0.157809 1198.09 1286.66 1.000
alpha{3} 6.080959 0.947238 4.217589 7.856650 6.008479 1203.76 1327.22 1.000
pinvar{all} 0.118662 0.000297 0.085221 0.150824 0.118414 966.86 1179.36 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 -13989.780834
Model 2: PositiveSelection -13989.780834
Model 0: one-ratio -14020.409681
Model 3: discrete -13832.709146
Model 7: beta -13833.456417
Model 8: beta&w>1 -13831.724136
Model 0 vs 1 61.2576939999999
Model 2 vs 1 0.0
Model 8 vs 7 3.464561999997386
