--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Sat Nov 19 01:15:13 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/274/Hsc70-5-PA/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/274/Hsc70-5-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/274/Hsc70-5-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/274/Hsc70-5-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -6762.67 -6778.60
2 -6762.83 -6778.26
--------------------------------------
TOTAL -6762.75 -6778.44
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/274/Hsc70-5-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/274/Hsc70-5-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/274/Hsc70-5-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} 1.142365 0.004460 1.018508 1.279946 1.141402 1261.32 1367.34 1.001
r(A<->C){all} 0.063453 0.000106 0.045425 0.085048 0.063129 1075.06 1109.57 1.000
r(A<->G){all} 0.239397 0.000515 0.195501 0.285261 0.238781 837.57 890.22 1.001
r(A<->T){all} 0.108232 0.000373 0.072535 0.148774 0.106861 811.58 850.21 1.000
r(C<->G){all} 0.029086 0.000030 0.018373 0.039906 0.028819 1075.69 1189.47 1.001
r(C<->T){all} 0.486673 0.000713 0.432994 0.536510 0.485808 798.22 858.80 1.000
r(G<->T){all} 0.073160 0.000124 0.052147 0.095207 0.072566 967.06 1054.43 1.001
pi(A){all} 0.220938 0.000077 0.204258 0.237830 0.220798 969.31 1098.05 1.000
pi(C){all} 0.295086 0.000084 0.277393 0.312273 0.295085 966.74 1102.95 1.000
pi(G){all} 0.289673 0.000094 0.271855 0.308754 0.289796 1177.93 1245.48 1.000
pi(T){all} 0.194302 0.000059 0.178792 0.208944 0.194406 1123.97 1131.86 1.000
alpha{1,2} 0.084933 0.000049 0.071485 0.098219 0.084758 1369.91 1431.08 1.000
alpha{3} 4.574438 1.022920 2.774277 6.579811 4.484073 1487.34 1494.17 1.000
pinvar{all} 0.358231 0.000744 0.304625 0.411738 0.358489 1091.67 1247.34 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 -6298.787654
Model 2: PositiveSelection -6298.787654
Model 0: one-ratio -6338.704008
Model 3: discrete -6288.661124
Model 7: beta -6292.126465
Model 8: beta&w>1 -6289.117973
Model 0 vs 1 79.83270799999991
Model 2 vs 1 0.0
Model 8 vs 7 6.016983999999866
Additional information for M7 vs M8:
Naive Empirical Bayes (NEB) analysis
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: D_melanogaster_Hsc70-5-PA)
Pr(w>1) post mean +- SE for w
660 N 0.995** 0.996
661 A 0.721 0.760
Bayes Empirical Bayes (BEB) analysis (Yang, Wong & Nielsen 2005. Mol. Biol. Evol. 22:1107-1118)
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: D_melanogaster_Hsc70-5-PA)
Pr(w>1) post mean +- SE for w
660 N 0.820 1.431 +- 0.511
661 A 0.640 1.214 +- 0.661
662 G 0.581 1.113 +- 0.721
