--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Thu May 03 15:07:15 WEST 2018
codeml.models=0 1 2 3 7 8
mrbayes.mpich=
mrbayes.ngen=1000000
tcoffee.alignMethod=MUSCLE
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/ADOPS1/DNG_N1/E_5/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N1/E_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N1/E_5/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/ADOPS1/DNG_N1/E_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -12239.74 -12286.21
2 -12238.53 -12291.36
--------------------------------------
TOTAL -12238.96 -12290.67
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N1/E_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N1/E_5/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/ADOPS1/DNG_N1/E_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 8.945854 0.287377 7.991090 10.034280 8.917087 515.01 651.12 1.000
r(A<->C){all} 0.041307 0.000027 0.030601 0.050829 0.041020 612.15 692.28 1.000
r(A<->G){all} 0.182715 0.000146 0.159813 0.205367 0.182464 320.64 508.08 1.001
r(A<->T){all} 0.050040 0.000035 0.038216 0.061534 0.049986 473.69 686.10 1.000
r(C<->G){all} 0.015137 0.000016 0.007830 0.023260 0.014929 969.73 971.29 1.006
r(C<->T){all} 0.681954 0.000243 0.653149 0.712402 0.682130 237.91 464.81 1.002
r(G<->T){all} 0.028848 0.000029 0.018325 0.039302 0.028618 563.16 731.43 1.000
pi(A){all} 0.347795 0.000072 0.332011 0.365015 0.347649 619.81 726.76 1.001
pi(C){all} 0.219274 0.000051 0.204842 0.233093 0.219387 735.50 777.57 1.000
pi(G){all} 0.240934 0.000058 0.225859 0.254923 0.240957 814.69 876.80 1.000
pi(T){all} 0.191997 0.000044 0.178945 0.204599 0.191875 500.92 709.56 1.000
alpha{1,2} 0.203233 0.000118 0.181688 0.223570 0.202619 994.21 1122.13 1.000
alpha{3} 4.540831 0.600213 3.153307 6.128505 4.454810 1209.16 1355.08 1.000
pinvar{all} 0.099068 0.000342 0.064354 0.136244 0.097965 1180.10 1214.44 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 -11431.863105
Model 2: PositiveSelection -11431.863109
Model 0: one-ratio -11466.23619
Model 3: discrete -11281.208712
Model 7: beta -11283.169663
Model 8: beta&w>1 -11283.172841
Model 0 vs 1 68.74616999999853
Model 2 vs 1 7.99999907030724E-6
Model 8 vs 7 0.0063559999980498105
