--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Sat May 26 20:36:21 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_A1/NS1_3/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_A1/NS1_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A1/NS1_3/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_A1/NS1_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -9540.29         -9587.01
2      -9538.48         -9587.22
--------------------------------------
TOTAL    -9539.02         -9587.12
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_A1/NS1_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A1/NS1_3/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_A1/NS1_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         7.689709    0.192014    6.820516    8.531677    7.688209    661.61    715.40    1.003
r(A<->C){all}   0.037382    0.000027    0.027550    0.047747    0.037164    962.57    999.52    1.003
r(A<->G){all}   0.236442    0.000258    0.206453    0.269944    0.235977    587.97    605.84    1.000
r(A<->T){all}   0.049584    0.000036    0.037847    0.060887    0.049352    809.32    921.08    1.000
r(C<->G){all}   0.027772    0.000034    0.016220    0.039132    0.027467    760.15    837.87    1.003
r(C<->T){all}   0.622841    0.000374    0.584901    0.659624    0.622924    560.61    564.87    1.000
r(G<->T){all}   0.025979    0.000038    0.014090    0.037590    0.025596    786.43    832.09    1.000
pi(A){all}      0.346046    0.000101    0.327313    0.365841    0.345736    816.31    898.89    1.000
pi(C){all}      0.231939    0.000072    0.214748    0.247624    0.231977    848.16    900.32    1.000
pi(G){all}      0.223508    0.000074    0.207531    0.240511    0.223223    674.55    809.90    1.001
pi(T){all}      0.198507    0.000061    0.182021    0.212751    0.198503    708.09    711.70    1.000
alpha{1,2}      0.207218    0.000159    0.183269    0.231107    0.206608   1319.11   1332.11    1.000
alpha{3}        6.173705    1.200914    4.048772    8.281133    6.080168   1184.29   1264.05    1.000
pinvar{all}     0.130637    0.000448    0.091646    0.173217    0.129923   1210.81   1257.89    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	-9224.478077
Model 2: PositiveSelection	-9224.478091
Model 0: one-ratio	-9305.724057
Model 3: discrete	-9122.163478
Model 7: beta	-9126.665226
Model 8: beta&w>1	-9123.912361


Model 0 vs 1	162.49195999999938

Model 2 vs 1	2.800000220304355E-5

Model 8 vs 7	5.505729999997129