--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Thu May 10 01:42:45 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_N2/NS2B_1/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N2/NS2B_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/NS2B_1/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_N2/NS2B_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -3451.65 -3496.60
2 -3450.42 -3497.60
--------------------------------------
TOTAL -3450.86 -3497.22
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N2/NS2B_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/NS2B_1/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_N2/NS2B_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 7.692794 0.385136 6.378891 8.815663 7.674388 728.93 870.12 1.000
r(A<->C){all} 0.063142 0.000161 0.039494 0.089352 0.062701 818.70 844.26 1.000
r(A<->G){all} 0.202987 0.000566 0.159866 0.251700 0.201726 634.74 659.61 1.002
r(A<->T){all} 0.059348 0.000150 0.035472 0.083629 0.058885 843.76 878.86 1.001
r(C<->G){all} 0.056813 0.000170 0.033409 0.083628 0.056158 622.28 629.85 1.000
r(C<->T){all} 0.602481 0.000947 0.542096 0.661560 0.602807 584.63 599.68 1.001
r(G<->T){all} 0.015229 0.000061 0.000955 0.030334 0.014028 826.84 831.91 1.000
pi(A){all} 0.326883 0.000254 0.296281 0.358824 0.326672 903.61 973.12 1.000
pi(C){all} 0.218763 0.000175 0.194054 0.245715 0.218259 972.81 1016.68 1.000
pi(G){all} 0.235769 0.000224 0.206766 0.265327 0.235499 749.72 901.39 1.001
pi(T){all} 0.218584 0.000186 0.190875 0.244032 0.218287 699.16 831.67 1.000
alpha{1,2} 0.254998 0.000742 0.205995 0.310829 0.253050 1063.62 1221.53 1.000
alpha{3} 3.372293 0.642241 1.993634 5.006694 3.278331 1191.74 1197.66 1.001
pinvar{all} 0.083321 0.000954 0.027060 0.145304 0.081817 1267.73 1275.58 1.002
------------------------------------------------------------------------------------------------------
* 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 -3196.495324
Model 2: PositiveSelection -3196.495331
Model 0: one-ratio -3198.09903
Model 3: discrete -3168.586784
Model 7: beta -3170.076891
Model 8: beta&w>1 -3170.078161
Model 0 vs 1 3.2074119999997492
Model 2 vs 1 1.4000000192027073E-5
Model 8 vs 7 0.002539999999498832
