--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Fri Nov 25 13:46:46 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-PD/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/1/14-3-3zeta-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PD/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-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -1343.20 -1378.56
2 -1341.42 -1380.48
--------------------------------------
TOTAL -1341.96 -1379.93
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/1/14-3-3zeta-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PD/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-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 0.477927 0.065319 0.141454 0.988819 0.412012 948.75 1008.96 1.000
r(A<->C){all} 0.069693 0.001475 0.003106 0.143031 0.063784 455.10 516.27 1.001
r(A<->G){all} 0.243666 0.017767 0.036892 0.510775 0.216142 170.62 220.06 1.011
r(A<->T){all} 0.065585 0.001437 0.002272 0.137898 0.059483 520.54 563.23 1.002
r(C<->G){all} 0.044733 0.000823 0.000657 0.101570 0.038560 439.97 605.20 1.001
r(C<->T){all} 0.559002 0.023770 0.273571 0.851358 0.568327 188.96 205.75 1.010
r(G<->T){all} 0.017320 0.000319 0.000043 0.051130 0.011605 763.09 866.70 1.000
pi(A){all} 0.279750 0.000269 0.247980 0.312542 0.279585 1054.58 1165.22 1.000
pi(C){all} 0.259495 0.000250 0.228881 0.289029 0.258881 1076.65 1234.12 1.000
pi(G){all} 0.260475 0.000243 0.229630 0.290096 0.259990 926.83 1047.63 1.000
pi(T){all} 0.200279 0.000205 0.171491 0.227611 0.200212 1054.52 1160.42 1.000
alpha{1,2} 0.092865 0.000793 0.033581 0.158529 0.091075 928.29 1007.01 1.000
alpha{3} 1.211923 0.406711 0.258565 2.457056 1.083655 1042.64 1079.11 1.000
pinvar{all} 0.825988 0.001185 0.757798 0.887158 0.830301 1061.04 1078.22 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
