def showAnalysis(self):
"""Analysis of current pKas"""
from PEATDB.Ekin.Titration import TitrationAnalyser
self.showHeader(menu=1)
DB = self.DB = self.connect()
t = TitrationAnalyser()
print '<div class="main">'
print '<p>Selected plots below reflect some of the analysis shown in the \
<a href="%s/paper_2010.pdf"> original paper</a> updated for the current dataset. </p>' %self.bindir
print '<a>The distributions shown are of the change in chemical shift over all\
detected titrations. `Reliable` pKas are those associated with\
the largest chemical shift changes in a titration curve and that meets the criteria defined in\
the paper. We define primary pKa values simply as the subset of the reliable pKa values \
that originate from titration curves with with only one titration.</a>'
sys.stdout.flush()
colnames = ['1H NMR','15N NMR','13C NMR']
for col in colnames:
p = t.extractpKas(DB,col,silent=True,minspan=0.06)
print '<div>'
print "<h2>%s: Distribution of Δδ for fitted pKa values</h2>" %col
img1 = t.analysepKas(p, silent=True, prefix=col, path=self.imagepath)
#t.makepKasTable(p)
print '<img src="%s/%s" align=center width=800 class="plot">' %(self.plotsdir, img1)
print '</div>'
sys.stdout.flush()
#compare nuclei
img2, img3 = t.compareNuclei(DB, '15N NMR', '1H NMR', titratable=False, silent=True, path=self.imagepath)
print '<p>Below is an analysis of the correspondence between fitted pKas for 1H and 15N \
where they are available for the same residue in the same protein. This is the same\
plot as figure 4 in the original paper updated for the current dataset.\
The plots are divided into reliable and other pKas for comparison.</p>'
print '<div>'
print '<center><img src="%s/%s" align=center width=600 class="plot"></center>' %(self.plotsdir, img2)
print '</div>'
print '<p>The same plot as above broken down by residue type and shown only for titratable\
residues.</p>'
print '<div>'
print '<center><img src="%s/%s" align=center width=600 class="plot"></center>' %(self.plotsdir, img3)
print '</div>'
self.footer()
return
from PEATDB.Ekin.Titration import TitrationAnalyser
from PEATDB.Base import PDatabase
from PEATDB.Ekin.Base import EkinProject
from PEATDB.DictEdit import DictEditor
import os
import pickle
cols = ['15N NMR', '1H NMR']
nuclnames = {'1H NMR':'H','15N NMR':'N'}
complete = ['HEWL', 'Bovine Beta-Lactoglobulin',
'Plastocyanin (Anabaena variabilis)',
'Plastocyanin (Phormidium)',
'Glutaredoxin', 'CexCD (Apo)',
'Protein G B1','Xylanase (Bacillus subtilus)']
col=cols[0]
nucl = nuclnames[col]
t = TitrationAnalyser()
#ghost mapping..
DB = PDatabase(server='peat.ucd.ie', username='******',
password='******', project='titration_db',
port=8080)
p=t.extractpKas(DB, col, names=['HEWL'], titratable=False, reliable=False, minspan=0.06)
t.mappKas(DB,col,p,names=['HEWL'],
nucleus=nucl,calculatespans=False)
from PEATDB.Ekin.Base import EkinProject
from PEATDB.DictEdit import DictEditor
import os
import pickle
cols = ['15N NMR', '1H NMR']
nuclnames = {'1H NMR': 'H', '15N NMR': 'N'}
complete = [
'HEWL', 'Bovine Beta-Lactoglobulin', 'Plastocyanin (Anabaena variabilis)',
'Plastocyanin (Phormidium)', 'Glutaredoxin', 'CexCD (Apo)', 'Protein G B1',
'Xylanase (Bacillus subtilus)'
]
col = cols[0]
nucl = nuclnames[col]
t = TitrationAnalyser()
#ghost mapping..
DB = PDatabase(server='peat.ucd.ie',
username='******',
password='******',
project='titration_db',
port=8080)
p = t.extractpKas(DB,
col,
names=['HEWL'],
titratable=False,
reliable=False,
minspan=0.06)
t.mappKas(DB, col, p, names=['HEWL'], nucleus=nucl, calculatespans=False)
