--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Thu Jun 07 12:07:48 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/NS4B_2/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_A2/NS4B_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A2/NS4B_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_A2/NS4B_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -6687.27 -6726.53
2 -6685.55 -6728.19
--------------------------------------
TOTAL -6686.08 -6727.67
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_A2/NS4B_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A2/NS4B_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_A2/NS4B_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} 7.086022 0.213811 6.199199 8.010584 7.074923 651.47 881.26 1.000
r(A<->C){all} 0.036961 0.000040 0.025454 0.049481 0.036649 469.25 668.20 1.000
r(A<->G){all} 0.201010 0.000297 0.167568 0.234849 0.200502 551.16 605.53 1.001
r(A<->T){all} 0.052393 0.000056 0.038390 0.067101 0.051964 1028.31 1047.27 1.000
r(C<->G){all} 0.019979 0.000041 0.008337 0.032960 0.019511 737.69 771.31 1.000
r(C<->T){all} 0.645368 0.000476 0.602254 0.686042 0.645778 477.87 524.41 1.000
r(G<->T){all} 0.044290 0.000069 0.028035 0.060297 0.043864 718.08 730.42 1.000
pi(A){all} 0.328788 0.000147 0.305801 0.352838 0.328779 851.50 958.28 1.000
pi(C){all} 0.235477 0.000107 0.214297 0.254388 0.235141 927.78 940.59 1.000
pi(G){all} 0.215657 0.000115 0.195662 0.238395 0.215572 936.27 977.87 1.000
pi(T){all} 0.220077 0.000096 0.200625 0.238400 0.219783 708.04 866.55 1.000
alpha{1,2} 0.203683 0.000184 0.177078 0.230548 0.202838 1195.20 1260.96 1.001
alpha{3} 4.693651 0.793826 3.049390 6.475750 4.601192 1451.36 1476.18 1.000
pinvar{all} 0.105541 0.000803 0.050173 0.160505 0.104978 1031.83 1266.41 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 -6262.79385
Model 2: PositiveSelection -6262.793736
Model 0: one-ratio -6309.157251
Model 3: discrete -6197.49739
Model 7: beta -6200.35853
Model 8: beta&w>1 -6200.364695
Model 0 vs 1 92.72680199999922
Model 2 vs 1 2.280000007885974E-4
Model 8 vs 7 0.012329999999565189
