--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Sat May 26 20:36:21 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/NS1_3/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_A1/NS1_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A1/NS1_3/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/NS1_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -9540.29 -9587.01
2 -9538.48 -9587.22
--------------------------------------
TOTAL -9539.02 -9587.12
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_A1/NS1_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A1/NS1_3/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/NS1_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 7.689709 0.192014 6.820516 8.531677 7.688209 661.61 715.40 1.003
r(A<->C){all} 0.037382 0.000027 0.027550 0.047747 0.037164 962.57 999.52 1.003
r(A<->G){all} 0.236442 0.000258 0.206453 0.269944 0.235977 587.97 605.84 1.000
r(A<->T){all} 0.049584 0.000036 0.037847 0.060887 0.049352 809.32 921.08 1.000
r(C<->G){all} 0.027772 0.000034 0.016220 0.039132 0.027467 760.15 837.87 1.003
r(C<->T){all} 0.622841 0.000374 0.584901 0.659624 0.622924 560.61 564.87 1.000
r(G<->T){all} 0.025979 0.000038 0.014090 0.037590 0.025596 786.43 832.09 1.000
pi(A){all} 0.346046 0.000101 0.327313 0.365841 0.345736 816.31 898.89 1.000
pi(C){all} 0.231939 0.000072 0.214748 0.247624 0.231977 848.16 900.32 1.000
pi(G){all} 0.223508 0.000074 0.207531 0.240511 0.223223 674.55 809.90 1.001
pi(T){all} 0.198507 0.000061 0.182021 0.212751 0.198503 708.09 711.70 1.000
alpha{1,2} 0.207218 0.000159 0.183269 0.231107 0.206608 1319.11 1332.11 1.000
alpha{3} 6.173705 1.200914 4.048772 8.281133 6.080168 1184.29 1264.05 1.000
pinvar{all} 0.130637 0.000448 0.091646 0.173217 0.129923 1210.81 1257.89 1.002
------------------------------------------------------------------------------------------------------
* 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 -9224.478077
Model 2: PositiveSelection -9224.478091
Model 0: one-ratio -9305.724057
Model 3: discrete -9122.163478
Model 7: beta -9126.665226
Model 8: beta&w>1 -9123.912361
Model 0 vs 1 162.49195999999938
Model 2 vs 1 2.800000220304355E-5
Model 8 vs 7 5.505729999997129
