--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Fri Nov 25 15:04:20 WET 2016
codeml.models=0 1 2 3 7 8
mrbayes.mpich=
mrbayes.ngen=1000000
tcoffee.alignMethod=CLUSTALW2
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/ADOPS/1/14-3-3zeta-PJ/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/1/14-3-3zeta-PJ/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PJ/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/ADOPS/1/14-3-3zeta-PJ/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -1342.81 -1383.83
2 -1341.12 -1382.53
--------------------------------------
TOTAL -1341.65 -1383.38
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/1/14-3-3zeta-PJ/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PJ/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/ADOPS/1/14-3-3zeta-PJ/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 0.476780 0.063051 0.152655 1.002599 0.408395 720.93 859.17 1.000
r(A<->C){all} 0.070402 0.001539 0.005375 0.145904 0.063982 441.79 479.66 1.000
r(A<->G){all} 0.236200 0.015525 0.037854 0.485439 0.211056 134.28 197.18 1.000
r(A<->T){all} 0.065136 0.001435 0.006683 0.142577 0.058541 428.13 482.49 1.004
r(C<->G){all} 0.045393 0.000819 0.002140 0.100972 0.039549 616.43 616.72 1.000
r(C<->T){all} 0.565716 0.020514 0.303397 0.848663 0.571163 162.65 183.51 1.000
r(G<->T){all} 0.017153 0.000301 0.000014 0.051937 0.011922 558.49 699.48 1.000
pi(A){all} 0.279983 0.000249 0.249437 0.310811 0.279229 992.66 1047.16 1.000
pi(C){all} 0.259685 0.000257 0.228701 0.290107 0.259279 1075.92 1150.07 1.000
pi(G){all} 0.259899 0.000250 0.229396 0.290424 0.259771 1074.32 1149.41 1.001
pi(T){all} 0.200434 0.000203 0.170247 0.226428 0.200408 880.29 1089.11 1.000
alpha{1,2} 0.094111 0.000797 0.036327 0.156475 0.091984 906.89 1098.06 1.000
alpha{3} 1.193212 0.384872 0.249971 2.419900 1.052090 867.19 955.70 1.000
pinvar{all} 0.826546 0.001175 0.758937 0.885881 0.830428 813.30 903.53 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 -1263.066771
Model 2: PositiveSelection -1263.066771
Model 0: one-ratio -1264.026193
Model 3: discrete -1263.063085
Model 7: beta -1263.3924
Model 8: beta&w>1 -1263.066768
Model 0 vs 1 1.9188439999998081
Model 2 vs 1 0.0
Model 8 vs 7 0.6512640000000829
