--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Thu Nov 10 18:46:50 WET 2016
codeml.models=0 1 2 3 7 8
mrbayes.mpich=
mrbayes.ngen=1000000
tcoffee.alignMethod=CLUSTALW2
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/ADOPS/191/CG8312-PA/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/191/CG8312-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/191/CG8312-PA/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/191/CG8312-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -9105.76         -9126.01
2      -9105.91         -9125.76
--------------------------------------
TOTAL    -9105.83         -9125.89
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/191/CG8312-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/191/CG8312-PA/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/191/CG8312-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         0.797308    0.001733    0.715572    0.877058    0.796028   1245.63   1373.32    1.000
r(A<->C){all}   0.085027    0.000102    0.065567    0.104218    0.084534    927.09    999.24    1.000
r(A<->G){all}   0.191224    0.000271    0.159482    0.223138    0.190815    748.12    809.51    1.000
r(A<->T){all}   0.106758    0.000256    0.076000    0.138981    0.106150    742.72    834.22    1.000
r(C<->G){all}   0.071431    0.000057    0.057510    0.086402    0.071185    949.61   1071.21    1.000
r(C<->T){all}   0.453254    0.000543    0.408258    0.498942    0.453114    674.83    729.80    1.000
r(G<->T){all}   0.092306    0.000137    0.071058    0.115565    0.091863   1055.36   1139.35    1.001
pi(A){all}      0.243624    0.000062    0.228348    0.259040    0.243516   1013.37   1097.30    1.000
pi(C){all}      0.298177    0.000063    0.282092    0.312819    0.298346   1030.66   1075.34    1.000
pi(G){all}      0.308598    0.000069    0.291241    0.323689    0.308632   1075.68   1105.99    1.000
pi(T){all}      0.149601    0.000038    0.137858    0.161733    0.149385    901.22    911.77    1.000
alpha{1,2}      0.164519    0.000231    0.135573    0.194509    0.164507   1279.15   1336.09    1.000
alpha{3}        4.088486    1.000038    2.261959    6.037891    3.953266    985.55   1157.79    1.003
pinvar{all}     0.326374    0.001165    0.259287    0.391647    0.328481   1079.13   1193.32    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	-7985.933295
Model 2: PositiveSelection	-7985.933295
Model 0: one-ratio	-8098.578686
Model 3: discrete	-7960.665157
Model 7: beta	-7967.58304
Model 8: beta&w>1	-7961.029397


Model 0 vs 1	225.29078200000004

Model 2 vs 1	0.0

Model 8 vs 7	13.107286000000386

Additional information for M7 vs M8:
Naive Empirical Bayes (NEB) analysis
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: D_melanogaster_CG8312-PA)

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

     9 S      0.919         1.616
    13 D      0.996**       1.723
    48 V      0.752         1.383
    93 A      0.924         1.624
   588 T      0.767         1.406
   668 A      0.940         1.646
   832 T      0.596         1.168

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: D_melanogaster_CG8312-PA)

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

     9 S      0.933         1.447 +- 0.231
    13 D      0.981*        1.490 +- 0.126
    48 V      0.867         1.380 +- 0.335
    52 A      0.622         1.090 +- 0.557
    93 A      0.929         1.445 +- 0.232
    96 T      0.681         1.183 +- 0.489
    97 T      0.595         1.091 +- 0.520
    98 A      0.629         1.129 +- 0.507
   484 S      0.667         1.187 +- 0.463
   588 T      0.853         1.376 +- 0.323
   635 T      0.531         1.042 +- 0.510
   668 A      0.927         1.444 +- 0.229
   832 T      0.778         1.304 +- 0.387
   833 S      0.728         1.214 +- 0.498