--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Wed Dec 20 02:57:21 WET 2017
codeml.models=
mrbayes.mpich=
mrbayes.ngen=1000000
tcoffee.alignMethod=MUSCLE
tcoffee.params=
tcoffee.maxSeqs=0
codeml.bin=codeml
mrbayes.tburnin=2500
codeml.dir=/usr/bin/
input.sequences=
mrbayes.pburnin=2500
mrbayes.bin=mb
tcoffee.bin=t_coffee
mrbayes.dir=/usr/bin/
tcoffee.dir=
tcoffee.minScore=3
input.fasta=/opt/ADOPS/DGA_B3/NS5_4/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DGA_B3/NS5_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_4/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/DGA_B3/NS5_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -22261.63 -22306.60
2 -22260.87 -22309.05
--------------------------------------
TOTAL -22261.18 -22308.44
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DGA_B3/NS5_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_4/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/DGA_B3/NS5_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 6.901823 0.105917 6.310940 7.577892 6.891951 289.93 479.11 1.001
r(A<->C){all} 0.036078 0.000011 0.029510 0.042357 0.035941 639.43 741.41 1.000
r(A<->G){all} 0.187926 0.000084 0.170803 0.205794 0.187432 481.29 548.73 1.001
r(A<->T){all} 0.049003 0.000017 0.041178 0.057169 0.049005 776.80 823.43 1.000
r(C<->G){all} 0.023166 0.000012 0.016130 0.029761 0.023030 809.36 858.00 1.001
r(C<->T){all} 0.674360 0.000143 0.651804 0.698135 0.674677 444.27 486.46 1.000
r(G<->T){all} 0.029466 0.000018 0.021531 0.037837 0.029239 539.00 696.26 1.000
pi(A){all} 0.361198 0.000046 0.347720 0.374376 0.361209 655.80 674.76 1.000
pi(C){all} 0.221810 0.000031 0.211592 0.233131 0.221724 589.21 719.72 1.001
pi(G){all} 0.236345 0.000037 0.225214 0.248683 0.236320 603.10 706.81 1.000
pi(T){all} 0.180646 0.000023 0.171572 0.190194 0.180616 721.33 766.58 1.000
alpha{1,2} 0.197757 0.000065 0.181236 0.212643 0.197520 1260.71 1301.89 1.000
alpha{3} 5.738891 0.740447 4.143632 7.400518 5.668143 923.80 1184.75 1.000
pinvar{all} 0.126623 0.000209 0.099024 0.154283 0.126642 959.77 1028.67 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: One dN/dS ratio for branches, -21597.040755
