--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Thu May 03 23:16:31 WEST 2018
codeml.models=
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/DNGB3/NS5_5/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DNGB3/NS5_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DNGB3/NS5_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/DNGB3/NS5_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -20308.63        -20359.61
2     -20311.87        -20346.48
--------------------------------------
TOTAL   -20309.28        -20358.92
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DNGB3/NS5_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DNGB3/NS5_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/DNGB3/NS5_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}         6.531718    0.109004    5.914085    7.197690    6.521873    410.83    417.93    1.004
r(A<->C){all}   0.042863    0.000016    0.035378    0.050781    0.042826    728.28    790.35    1.000
r(A<->G){all}   0.185676    0.000095    0.166779    0.204497    0.185822    443.92    445.33    1.000
r(A<->T){all}   0.043253    0.000020    0.034707    0.052235    0.043331    500.84    653.51    1.000
r(C<->G){all}   0.028639    0.000017    0.020885    0.036806    0.028488    777.07    839.15    1.000
r(C<->T){all}   0.676374    0.000172    0.652171    0.703560    0.676458    396.06    407.46    1.000
r(G<->T){all}   0.023194    0.000019    0.014690    0.031119    0.023106    677.38    707.56    1.000
pi(A){all}      0.356881    0.000049    0.342716    0.370494    0.357050    809.95    824.91    1.000
pi(C){all}      0.219329    0.000029    0.209532    0.230181    0.219213    828.70    864.42    1.001
pi(G){all}      0.240595    0.000038    0.229385    0.253429    0.240683    693.14    763.98    1.003
pi(T){all}      0.183195    0.000027    0.173244    0.193327    0.183210    601.17    649.10    1.000
alpha{1,2}      0.186403    0.000060    0.170810    0.201248    0.186128   1135.38   1240.32    1.000
alpha{3}        5.000369    0.604936    3.613205    6.474755    4.910508   1236.26   1314.68    1.000
pinvar{all}     0.122852    0.000240    0.092680    0.152978    0.122416   1231.02   1232.72    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: One dN/dS ratio for branches, 	-17822.477632