--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Fri Dec 09 19:06:12 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/442/Zasp52-PX/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/442/Zasp52-PX/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/442/Zasp52-PX/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/442/Zasp52-PX/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -17492.12 -17504.38
2 -17491.51 -17505.99
--------------------------------------
TOTAL -17491.77 -17505.48
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/442/Zasp52-PX/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/442/Zasp52-PX/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/442/Zasp52-PX/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 0.526557 0.000550 0.478922 0.570193 0.526054 1062.77 1199.39 1.000
r(A<->C){all} 0.074316 0.000066 0.058248 0.089894 0.074127 1045.79 1115.35 1.001
r(A<->G){all} 0.227114 0.000219 0.198812 0.256377 0.226743 852.69 921.04 1.000
r(A<->T){all} 0.178340 0.000238 0.147499 0.207461 0.177984 987.49 1072.11 1.000
r(C<->G){all} 0.057667 0.000036 0.046759 0.069950 0.057427 1190.73 1209.92 1.000
r(C<->T){all} 0.383968 0.000338 0.348981 0.419341 0.384073 894.89 935.04 1.000
r(G<->T){all} 0.078595 0.000088 0.060207 0.096855 0.078452 1044.99 1105.94 1.000
pi(A){all} 0.233437 0.000025 0.224114 0.243428 0.233430 1004.00 1070.69 1.000
pi(C){all} 0.334129 0.000030 0.323779 0.345398 0.334045 1118.44 1123.70 1.000
pi(G){all} 0.263307 0.000027 0.252902 0.273093 0.263317 1161.91 1196.19 1.000
pi(T){all} 0.169128 0.000018 0.160294 0.176869 0.169133 1098.34 1115.85 1.000
alpha{1,2} 0.150241 0.000175 0.123181 0.175005 0.149525 1336.99 1376.68 1.000
alpha{3} 5.882425 1.631466 3.586137 8.445575 5.717311 1293.15 1341.47 1.000
pinvar{all} 0.399978 0.000693 0.348814 0.452827 0.400995 1259.90 1309.50 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 -15475.649296
Model 2: PositiveSelection -15475.649296
Model 0: one-ratio -15653.204243
Model 3: discrete -15473.799784
Model 7: beta -15475.812597
Model 8: beta&w>1 -15473.833531
Model 0 vs 1 355.1098940000011
Model 2 vs 1 0.0
Model 8 vs 7 3.9581319999997504
