--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Wed Nov 16 02:29:09 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/241/endos-PA/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/241/endos-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/241/endos-PA/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/241/endos-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -1034.72 -1052.43
2 -1034.72 -1057.95
--------------------------------------
TOTAL -1034.72 -1057.26
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/241/endos-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/241/endos-PA/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/241/endos-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 0.864909 0.021560 0.606028 1.166137 0.850675 1069.18 1219.70 1.000
r(A<->C){all} 0.059170 0.000645 0.014575 0.109451 0.055984 730.17 756.21 1.000
r(A<->G){all} 0.161766 0.002844 0.068365 0.263594 0.154507 481.83 510.35 1.000
r(A<->T){all} 0.147841 0.004031 0.039627 0.276007 0.139888 526.97 537.51 1.000
r(C<->G){all} 0.027423 0.000152 0.006259 0.052005 0.025608 1111.26 1117.14 1.000
r(C<->T){all} 0.560160 0.007372 0.400017 0.728563 0.558670 368.66 405.90 1.000
r(G<->T){all} 0.043640 0.000607 0.004498 0.091908 0.039432 851.11 898.79 1.000
pi(A){all} 0.263122 0.000539 0.216968 0.305883 0.262279 906.51 945.46 1.000
pi(C){all} 0.320799 0.000553 0.271287 0.365587 0.321433 766.66 1033.94 1.000
pi(G){all} 0.296338 0.000547 0.249027 0.340836 0.296156 1061.71 1100.42 1.000
pi(T){all} 0.119740 0.000274 0.088736 0.153414 0.118758 623.80 807.86 1.000
alpha{1,2} 0.108833 0.000752 0.062121 0.165628 0.106103 1249.72 1375.36 1.000
alpha{3} 2.167137 0.669027 0.897424 3.785750 2.036796 1351.95 1374.40 1.000
pinvar{all} 0.329113 0.007477 0.162861 0.494978 0.333377 1282.45 1317.93 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 -947.477906
Model 2: PositiveSelection -947.477906
Model 0: one-ratio -954.749766
Model 3: discrete -944.892316
Model 7: beta -944.940117
Model 8: beta&w>1 -944.940556
Model 0 vs 1 14.543720000000121
Model 2 vs 1 0.0
Model 8 vs 7 8.780000000569999E-4
