--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Wed Nov 23 05:12:58 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/304/mfas-PB/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/304/mfas-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/304/mfas-PB/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/304/mfas-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -8986.85         -9006.27
2      -8987.08         -9006.17
--------------------------------------
TOTAL    -8986.96         -9006.23
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/304/mfas-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/304/mfas-PB/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/304/mfas-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         1.079804    0.003170    0.968693    1.190345    1.079073   1160.05   1242.69    1.000
r(A<->C){all}   0.121766    0.000158    0.097721    0.145155    0.121324   1049.78   1087.23    1.000
r(A<->G){all}   0.244307    0.000404    0.206494    0.284402    0.243860    868.81    890.34    1.000
r(A<->T){all}   0.080266    0.000205    0.052570    0.108570    0.079504    942.16   1016.26    1.001
r(C<->G){all}   0.061223    0.000051    0.046892    0.074990    0.061219   1052.72   1061.81    1.000
r(C<->T){all}   0.414364    0.000541    0.369476    0.456756    0.414225    842.52    915.39    1.001
r(G<->T){all}   0.078073    0.000100    0.057415    0.096388    0.077820   1128.44   1141.06    1.000
pi(A){all}      0.213477    0.000062    0.197693    0.228886    0.213471   1240.28   1242.99    1.003
pi(C){all}      0.324493    0.000075    0.307459    0.341454    0.324421   1104.86   1164.87    1.000
pi(G){all}      0.269644    0.000071    0.253382    0.286132    0.269327   1247.60   1286.70    1.002
pi(T){all}      0.192386    0.000051    0.178181    0.205872    0.192184   1261.66   1297.30    1.000
alpha{1,2}      0.140794    0.000108    0.121156    0.161411    0.140344   1272.87   1294.15    1.000
alpha{3}        4.204048    0.875848    2.597478    6.114617    4.094179   1195.29   1294.01    1.000
pinvar{all}     0.372771    0.000724    0.319546    0.423537    0.372901   1036.32   1176.11    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	-8345.127655
Model 2: PositiveSelection	-8345.127673
Model 0: one-ratio	-8444.319257
Model 3: discrete	-8335.489476
Model 7: beta	-8342.808923
Model 8: beta&w>1	-8336.492511


Model 0 vs 1	198.38320399999793

Model 2 vs 1	3.600000127335079E-5

Model 8 vs 7	12.632824000000255

Additional information for M7 vs M8:
Naive Empirical Bayes (NEB) analysis
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_mfas-PB)

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

    24 G      0.553         1.003 +- 0.578
    37 Q      0.748         1.273 +- 0.402
    51 S      0.853         1.376 +- 0.306
   119 S      0.620         1.147 +- 0.465
   123 A      0.652         1.153 +- 0.493
   253 M      0.891         1.407 +- 0.274
   458 H      0.743         1.274 +- 0.395
   479 D      0.747         1.261 +- 0.423
   562 N      0.550         1.062 +- 0.503
   696 N      0.671         1.207 +- 0.431
   702 S      0.796         1.304 +- 0.400