--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Fri Nov 25 15:26:45 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-PL/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/1/14-3-3zeta-PL/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PL/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-PL/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -1341.76 -1381.22
2 -1344.31 -1389.71
--------------------------------------
TOTAL -1342.38 -1389.02
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/1/14-3-3zeta-PL/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PL/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-PL/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 0.485009 0.063287 0.146257 1.001772 0.416285 891.72 895.63 1.000
r(A<->C){all} 0.068007 0.001572 0.000256 0.141216 0.060526 324.93 460.01 1.000
r(A<->G){all} 0.230654 0.015458 0.036083 0.482491 0.212445 201.41 266.37 1.001
r(A<->T){all} 0.064841 0.001531 0.005098 0.139618 0.057952 476.41 508.85 1.001
r(C<->G){all} 0.044280 0.000779 0.000058 0.096720 0.039213 333.93 394.36 1.001
r(C<->T){all} 0.574188 0.022134 0.288488 0.857889 0.572071 284.64 326.10 1.001
r(G<->T){all} 0.018030 0.000336 0.000004 0.056166 0.012076 613.81 728.16 1.000
pi(A){all} 0.280672 0.000267 0.249103 0.310808 0.280443 1083.40 1122.88 1.001
pi(C){all} 0.259480 0.000251 0.228249 0.289560 0.259411 1215.23 1292.76 1.000
pi(G){all} 0.259909 0.000255 0.230279 0.292257 0.259780 978.81 1082.22 1.002
pi(T){all} 0.199939 0.000212 0.173770 0.229793 0.199269 1087.76 1126.84 1.000
alpha{1,2} 0.093722 0.000843 0.035796 0.156225 0.091761 980.31 994.48 1.001
alpha{3} 1.191803 0.399384 0.299157 2.482751 1.059195 737.12 851.18 1.000
pinvar{all} 0.826061 0.001154 0.761418 0.890943 0.829741 1073.12 1097.42 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
