--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Fri Nov 25 13:23:56 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-PB/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/1/14-3-3zeta-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PB/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-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -1544.28 -1567.13
2 -1544.31 -1565.61
--------------------------------------
TOTAL -1544.29 -1566.64
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/1/14-3-3zeta-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PB/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-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 0.245856 0.001604 0.174180 0.325750 0.241814 1136.30 1318.65 1.000
r(A<->C){all} 0.113183 0.001243 0.049168 0.182604 0.109564 846.81 852.88 1.000
r(A<->G){all} 0.153348 0.001798 0.079640 0.240865 0.148999 811.48 856.54 1.000
r(A<->T){all} 0.066514 0.001006 0.012708 0.130478 0.062035 755.27 884.75 1.000
r(C<->G){all} 0.063165 0.000684 0.017561 0.114195 0.060155 884.58 960.25 1.001
r(C<->T){all} 0.553864 0.005036 0.409065 0.684867 0.555828 666.32 723.35 1.000
r(G<->T){all} 0.049926 0.000809 0.004077 0.103858 0.045310 858.11 927.24 1.000
pi(A){all} 0.285634 0.000263 0.254883 0.317959 0.285132 1182.12 1247.07 1.000
pi(C){all} 0.260975 0.000235 0.233004 0.293073 0.260752 1171.72 1183.73 1.000
pi(G){all} 0.258169 0.000240 0.227530 0.288645 0.258184 1228.06 1273.73 1.000
pi(T){all} 0.195222 0.000197 0.168133 0.222360 0.195008 961.99 1200.21 1.000
alpha{1,2} 0.056728 0.001797 0.000108 0.133540 0.048256 1004.00 1252.50 1.000
alpha{3} 2.093251 0.661590 0.714309 3.649766 1.970407 1230.32 1365.66 1.000
pinvar{all} 0.476075 0.008265 0.291909 0.633806 0.486202 1308.58 1341.06 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 -1451.36118
Model 2: PositiveSelection -1451.36118
Model 0: one-ratio -1458.92382
Model 3: discrete -1451.332921
Model 7: beta -1451.333746
Model 8: beta&w>1 -1451.361179
Model 0 vs 1 15.125279999999748
Model 2 vs 1 0.0
Model 8 vs 7 0.054865999999947235
