--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Mon Feb 12 22:49:27 WET 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=/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/HIV1_N2/POL_1_5/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/HIV1_N2/POL_1_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/HIV1_N2/POL_1_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/ADOPS/HIV1_N2/POL_1_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -30038.49        -30091.34
2     -30046.23        -30085.17
--------------------------------------
TOTAL   -30039.18        -30090.65
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/HIV1_N2/POL_1_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/HIV1_N2/POL_1_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/ADOPS/HIV1_N2/POL_1_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}         3.189075    0.009290    3.011557    3.386944    3.185564   1212.34   1248.47    1.000
r(A<->C){all}   0.074695    0.000015    0.067392    0.082392    0.074649    481.89    577.30    1.002
r(A<->G){all}   0.338452    0.000174    0.313705    0.364841    0.338507    357.92    391.29    1.001
r(A<->T){all}   0.032293    0.000006    0.027730    0.037102    0.032160    633.70    721.35    1.001
r(C<->G){all}   0.033943    0.000014    0.026340    0.040936    0.033830    590.08    685.87    1.000
r(C<->T){all}   0.485622    0.000208    0.455758    0.511951    0.485944    403.62    407.79    1.000
r(G<->T){all}   0.034994    0.000011    0.028866    0.041984    0.034890    558.76    597.87    1.000
pi(A){all}      0.409532    0.000051    0.396073    0.423361    0.409460    497.21    530.81    1.000
pi(C){all}      0.170107    0.000033    0.159062    0.181565    0.170054    391.93    448.86    1.000
pi(G){all}      0.209165    0.000034    0.197256    0.219914    0.209206    545.95    566.98    1.000
pi(T){all}      0.211195    0.000036    0.199195    0.222486    0.210963    569.08    611.40    1.000
alpha{1,2}      0.306852    0.000278    0.276167    0.342160    0.305701    897.35    978.45    1.001
alpha{3}        2.515981    0.064464    2.027365    2.989511    2.498368   1176.14   1194.64    1.000
pinvar{all}     0.284499    0.000315    0.250552    0.318349    0.284653    907.58   1043.34    1.001
------------------------------------------------------------------------------------------------------
* 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	-29472.106147
Model 2: PositiveSelection	-29397.898141
Model 0: one-ratio	-30873.153812
Model 3: discrete	-29263.38663
Model 7: beta	-29309.268156
Model 8: beta&w>1	-29205.096093


Model 0 vs 1	2802.0953300000037

Model 2 vs 1	148.41601199999423

Additional information for M1 vs M2:
Naive Empirical Bayes (NEB) analysis
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: 0206.BF.x.LA13BF17.KU168268_)

            Pr(w>1)     post mean +- SE for w

    16 P      0.958*        2.779
    20 A      0.907         2.684
    33 R      0.575         2.069
    40 A      0.975*        2.812
    41 L      0.995**       2.849
    42 S      0.993**       2.845
    43 F      0.881         2.636
   106 L      1.000**       2.858
   264 D      0.999**       2.856
   303 S      0.998**       2.854
   352 K      1.000**       2.857
   386 Q      1.000**       2.857
   427 A      0.710         2.319
   475 Q      0.921         2.710
   498 M      0.872         2.620
   517 A      0.839         2.558
   593 Q      0.825         2.533
   609 S      0.964*        2.790
   624 N      1.000**       2.857
   695 T      1.000**       2.858
   820 S      0.684         2.271
   825 A      0.648         2.205

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: 0206.BF.x.LA13BF17.KU168268_)

            Pr(w>1)     post mean +- SE for w

    16 P      0.969*        2.464 +- 0.280
    20 A      0.940         2.419 +- 0.372
    33 R      0.734         2.106 +- 0.670
    40 A      0.986*        2.489 +- 0.203
    41 L      0.996**       2.504 +- 0.140
    42 S      0.996**       2.504 +- 0.142
    43 F      0.918         2.386 +- 0.425
   106 L      1.000**       2.510 +- 0.101
   264 D      0.999**       2.509 +- 0.111
   303 S      0.999**       2.508 +- 0.115
   352 K      1.000**       2.510 +- 0.104
   386 Q      1.000**       2.510 +- 0.105
   427 A      0.833         2.256 +- 0.568
   475 Q      0.955*        2.442 +- 0.326
   498 M      0.953*        2.437 +- 0.328
   517 A      0.902         2.362 +- 0.458
   518 Q      0.679         2.019 +- 0.701
   576 V      0.678         2.018 +- 0.702
   593 Q      0.907         2.368 +- 0.448
   609 S      0.969*        2.464 +- 0.279
   624 N      1.000**       2.510 +- 0.104
   695 T      1.000**       2.510 +- 0.101
   820 S      0.836         2.260 +- 0.563
   825 A      0.826         2.243 +- 0.575


Model 8 vs 7	208.34412599999632

Additional information for M7 vs M8:
Naive Empirical Bayes (NEB) analysis
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: 0206.BF.x.LA13BF17.KU168268_)

            Pr(w>1)     post mean +- SE for w

    16 P      0.997**       2.271
    20 A      0.993**       2.265
    33 R      0.934         2.171
    40 A      0.999**       2.275
    41 L      1.000**       2.276
    42 S      1.000**       2.276
    43 F      0.986*        2.253
   106 L      1.000**       2.276
   264 D      1.000**       2.276
   276 T      0.537         1.544
   303 S      1.000**       2.276
   348 E      0.582         1.615
   352 K      1.000**       2.276
   386 Q      1.000**       2.276
   427 A      0.973*        2.234
   475 Q      0.995**       2.269
   498 M      0.998**       2.273
   517 A      0.987*        2.255
   518 Q      0.974*        2.235
   576 V      0.976*        2.237
   593 Q      0.989*        2.259
   609 S      0.996**       2.269
   624 N      1.000**       2.276
   695 T      1.000**       2.276
   820 S      0.978*        2.241
   825 A      0.980*        2.245

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: 0206.BF.x.LA13BF17.KU168268_)

            Pr(w>1)     post mean +- SE for w

    16 P      0.992**       2.487 +- 0.143
    20 A      0.983*        2.473 +- 0.208
    33 R      0.888         2.319 +- 0.511
    40 A      0.996**       2.493 +- 0.105
    41 L      0.999**       2.498 +- 0.051
    42 S      0.999**       2.498 +- 0.059
    43 F      0.974*        2.459 +- 0.254
   106 L      1.000**       2.500 +- 0.001
   264 D      1.000**       2.500 +- 0.024
   303 S      1.000**       2.499 +- 0.030
   352 K      1.000**       2.500 +- 0.012
   386 Q      1.000**       2.500 +- 0.014
   427 A      0.938         2.401 +- 0.386
   475 Q      0.982*        2.471 +- 0.213
   498 M      0.977*        2.464 +- 0.236
   517 A      0.969*        2.450 +- 0.278
   518 Q      0.768         2.133 +- 0.668
   576 V      0.772         2.139 +- 0.664
   593 Q      0.960*        2.437 +- 0.310
   609 S      0.993**       2.489 +- 0.135
   624 N      1.000**       2.500 +- 0.012
   695 T      1.000**       2.500 +- 0.001
   820 S      0.930         2.388 +- 0.409
   825 A      0.925         2.380 +- 0.421