def add(self, statistics, plotType):
logger.info("Registering plot function %s" % statistics)
if not rS.isRegistered(statistics):
logger.handleWarning("Caution, the statistics is unknown : %s" % statistics)
return False
self.all.append(statistics)
if plotType=="Multiple":
newPlotFunc = self.getMultiPlotFunction(statistics)
newPlotFunc = new.instancemethod(newPlotFunc, None, self.cls)
setattr(self.cls, newPlotFunc.__name__, newPlotFunc)
elif plotType=="Histo3D":
newPlotFunc = self.getHisto3DPlotFunction(statistics)
newPlotFunc = new.instancemethod(newPlotFunc, None, self.cls)
setattr(self.cls, "%sHisto3D" % newPlotFunc.__name__, newPlotFunc)
else:
logger.handleWarning("Caution, the statistics plot type is unknown : %s" % plotType)
pass
self.types.setdefault(statistics, set()).add(plotType)
self.allTypes.add(plotType)
return True
def checkValidity(self):
logger.info("Name :\t%s" % self.name)
allValid=True
for aspect in self.GPtoGO:
valid=True
for gp in self.GPtoGO[aspect]:
for go in self.GPtoGO[aspect][gp]:
if not gp in self.GOtoGP[aspect][go]:
logger.handleWarning ("%s not found in GOtoGP[%s][%s]" % (gp,aspect,go))
valid=False
for go in self.GOtoGP[aspect]:
for gp in self.GOtoGP[aspect][go]:
if not go in self.GPtoGO[aspect][gp]:
logger.handleWarning ("%s not found in GPtoGO[%s][%s]" % (go,aspect,gp))
valid=False
if valid:
logger.info ("%s : is valid" % (aspect))
allValid = allValid and valid
return allValid
def extract_Affy(fileName,
G,
refSet=None,
GO_columns=[30, 31, 32],
filetype="Affy",
delimiter=',',
quoting=csv.QUOTE_ALL):
fileName = checkForZip(fileName)
if (not os.path.exists(fileName)):
raise IOError(fileName + " does not exist and is required ")
#sniff and seek dialect
csvfile = readFile(fileName)
hasRef = None
if refSet:
hasRef = dict(izip(refSet, refSet))
GenetoGO, GOtoGene = dict(), dict()
for aspect in G.aspect:
GenetoGO[aspect], GOtoGene[aspect] = dict(), dict()
#Skip comments
row = csvfile.readline()
while row[0] == '#':
row = csvfile.readline()
#Read Header
header = row
#rd=list(csv.reader(f))
csv.register_dialect('format', delimiter=delimiter, quoting=quoting)
rd = csv.reader(csvfile, dialect='format')
for row in rd:
#Read gene product id
g = row[0]
if hasRef and not hasRef.has_key(g):
logger.handleWarning(
"gene product %s is not in the reference set, skip it " % g)
continue
for aspect, i in zip(
['biological_process', 'cellular_component', 'molecular_function'],
GO_columns):
for item in row[i].split('///'):
if not item == "---" and not len(item.strip()) == 0:
go = "GO:%07d" % int(item.split('//')[0].replace('/', ''))
go, aspect = G.get_GOAlternative(go, nameSpace=True)
if not aspect:
logger.handleWarning(
"term %s is not in GO graph, skip it " % go)
continue
GenetoGO[aspect].setdefault(g, set([])).add(go)
GOtoGene[aspect].setdefault(go, set([])).add(g)
return GenetoGO, GOtoGene
def extract_GO2GP(fileName,
G,
refSet=None,
sep1='\t',
sep2=',',
comments='#',
skiprows=0):
"""
Read a functional annotation mapping file of the form
GO_ID sep Gene_ID,Gene_ID
sep is \t by default
"""
fileName = str(checkForZip(fileName))
if (not os.path.exists(fileName)):
raise IOError(fileName + " does not exist and is required ")
hasRef = None
if refSet:
hasRef = dict(izip(refSet, refSet))
GenetoGO, GOtoGene = dict(), dict()
for aspect in G.aspect:
GenetoGO[aspect], GOtoGene[aspect] = dict(), dict()
data = loadtxt(fileName,
dtype="S",
usecols=[0, 1],
delimiter=sep1,
comments=comments,
skiprows=skiprows)
for go, GP in data:
if not go.find('GO:') == 0:
continue
#Get the alternative term if any and its GO aspect
term, aspect = G.get_GOAlternative(go, nameSpace=True)
if not aspect:
logger.handleWarning("term %s is not in GO graph, skip it " %
(term))
continue
for gp in GP.split(sep2):
gp = gp.strip()
if not hasRef is None and not hasRef.has_key(gp):
logger.handleWarning(
"gene product %s is not in the reference set, skip it " %
gp)
continue
GenetoGO[aspect].setdefault(gp, set([])).add(go)
GOtoGene[aspect].setdefault(go, set([])).add(gp)
return GenetoGO, GOtoGene
def save(self, fileName):
import shelve
try:
logger.info("File :\t%s" % fileName)
shelf = shelve.open(fileName, protocol=-1)
shelf['fileName'] = fileName
for k, v in self.items():
shelf[k] = v
shelf.close()
self.status = "Saved"
except Exception, e:
logger.handleWarning("Unable to save project %s: %s" %
(fileName, str(e)))
def load(self, fileName):
import shelve
try:
logger.info("File :\t%s" % fileName)
shelf = shelve.open(fileName, protocol=-1)
for k, v in shelf.items():
self[k] = v
shelf.close()
self.status = "Loaded"
except Exception, e:
logger.handleWarning("Unable to load project %s: %s" %
(fileName, str(e)))
def GOSet_PWSimilarity(G, GO1, GO2, metric="GS2", **kargs):
"""
Calculates pairwise semantic similarity scores between two given annotation sets
"""
if metric=="GS2":
sim, l=G.GS2([G.GOtoInt(GO1), G.GOtoInt(GO2)])
elif metric=="CzekanowskiDice":
sim = G.CzekanowskiDice(G.GOtoInt(GO1), G.GOtoInt(GO2))
l=[sim,sim]
elif metric=="Resnik":
sim,l = G.Resnik(G.GOtoInt(GO1), G.GOtoInt(GO2), kargs.get('IC', dict()))
else:
logger.handleWarning ("Sorry, unknown semnatic similarity %s " % metric)
sim,l=None,None
return sim, l
def GOSet_Similarity(G, GO, metric="GS2", **kargs):
"""
Calculates pairwise semantic similarity scores between GO terms in a given annotation set
"""
if len(GO)<2:
allD=list([1.])
else:
if metric=="GS2":
allD=[ G.GS2([G.GOtoInt([g1]), G.GOtoInt([g2])])[0] for i,g1 in enumerate(GO) for j,g2 in enumerate(GO) if i <j ]
elif metric=="CzekanowskiDice":
allD=[ G.CzekanowskiDice(G.GOtoInt([g1]), G.GOtoInt([g2])) for i,g1 in enumerate(GO) for j,g2 in enumerate(GO) if i <j ]
elif metric=="Resnik":
allD=[ G.Resnik(G.GOtoInt([g1]), G.GOtoInt([g2]), kargs.get('IC', dict()))[0] for i,g1 in enumerate(GO) for j,g2 in enumerate(GO) if i <j ]
else:
logger.handleWarning ("Sorry, unknown semnatic similarity %s " % metric)
allD=None
return allD
def extract_SCOP(fileName, G, refSet=None):
fileName = checkForZip(fileName)
if (not os.path.exists(fileName)):
raise IOError(fileName + " does not exist and is required ")
hasRef = None
if refSet:
hasRef = dict(izip(refSet, refSet))
GenetoGO, GOtoGene = dict(), dict()
for aspect in G.aspect:
GenetoGO[aspect], GOtoGene[aspect] = dict(), dict()
rd = csv.reader(readFile(fileName), delimiter=";")
header = rd.next()
for row in rd:
#Read gene product id
g = row[0]
g = row[header.index('domScop')]
go = row[header.index('termGo')]
if hasRef and not hasRef.has_key(g):
logger.handleWarning(
"gene product %s is not in the reference set, skip it " % g)
continue
if go.find('GO:') == 0:
#Get the alternative term if any and its GO aspect
go, aspect = G.get_GOAlternative(go, nameSpace=True)
if not aspect:
logger.handleWarning("term %s is not in GO graph, skip it " %
term)
continue
GenetoGO[aspect].setdefault(g, set([])).add(go)
GOtoGene[aspect].setdefault(go, set([])).add(g)
return GenetoGO, GOtoGene
def GO_Similarity(G, allGO, metric="GS2", **kargs):
"""
Calculates pairwise semantic similarity scores in a list of annotation sets
"""
if len(allGO)<2:
sim=1.0
l=[1.0]
else:
if metric=="GS2":
sim,l=G.GS2( [G.GOtoInt(GO) for GO in allGO ])
elif metric=="CzekanowskiDice":
allGO=[G.GOtoInt(GO) for GO in allGO ]
allD=dict()
l=list()
for i,GO1 in enumerate(allGO):
foo=[allD.setdefault(sort([i,j])[0],dict()).setdefault(sort([i,j])[1], G.CzekanowskiDice(GO1, GO2)) for j,GO2 in enumerate(allGO) if not j==i]
l.append(mean(foo))
sim=mean(l)
elif metric=="Resnik":
allGO=[G.GOtoInt(GO) for GO in allGO ]
allD=dict()
l=list()
for i,GO1 in enumerate(allGO):
foo=[allD.setdefault(sort([i,j])[0],dict()).setdefault(sort([i,j])[1], G.Resnik(GO1, GO2, kargs.get('IC', dict()))) for j,GO2 in enumerate(allGO) if not j==i]
l.append(mean(foo))
sim=mean(l)
else:
logger.handleWarning ("Sorry, unknown semnatic similarity %s " % metric)
sim,l=None,None
return sim,l
def extract_GAF(fileName, G, refSet=None):
fileName = checkForZip(fileName)
if (not os.path.exists(fileName)):
raise IOError(fileName + " does not exist and is required ")
hasRef = None
if refSet:
refRef = dict(izip(refSet, refSet))
GenetoGO, GOtoGene = dict(), dict()
for aspect in G.aspect:
GenetoGO[aspect], GOtoGene[aspect] = dict(), dict()
data, GAF_col = readGAF_2(fileName)
for row in data:
#g=row[GAF_col.index("DB Object Symbol")]
g = ".".join([
row[GAF_col.index("Taxon(|taxon)")][6:],
row[GAF_col.index("DB Object Symbol")]
])
go = row[GAF_col.index('GO ID')]
if not row[GAF_col.index('Qualifier')].find('NOT') == -1:
logger.handleWarning(
"go term %s for gene product %s is qualified as NOT: ignored" %
(go, g))
continue
if hasRef and not hasRef.has_key(g):
logger.handleWarning(
"gene product %s is not in the reference set, skip it " % g)
continue
if go.find('GO:') == 0:
go, aspect = G.get_GOAlternative(go, nameSpace=True)
if not aspect:
logger.handleWarning("term %s is not in GO graph, skip it " %
go)
continue
GenetoGO[aspect].setdefault(g, set([])).add(go)
GOtoGene[aspect].setdefault(go, set([])).add(g)
return GenetoGO, GOtoGene
def add(self, fileName, refType="Fasta"):
if self.fileName == '':
self.fileName = fileName
self.refType = refType
else:
if type(self.fileName) == list:
self.fileName.append(fileName)
self.refType.append(refType)
else:
self.fileName = [self.fileName, fileName]
self.refType = [self.refType, refType]
fileName = checkForZip(fileName)
if (not os.path.exists(fileName)):
logger.handleFatal(fileName + " does not exist and is required ")
logger.info("Organism :\t%s" % self.organism)
logger.info("%s file :\t%s " % (refType, fileName))
try:
#Use fasta file to define the reference set
if refType == "Fasta":
from Bio import SeqIO
allID = set([
rec.name.split(";")[0].split(":")[-1]
for rec in SeqIO.parse(readFile(fileName), "fasta")
])
self.update(allID)
#Use a simple text file to define the reference set, first column is chosen by default
elif refType == "Text":
allID = set([
r[0] for r in csv.reader(readFile(fileName), delimiter=";")
])
self.update(allID)
#Use a GO annotation file to define the reference set
elif refType == "GAF":
from AIGO.IO import readGAF_2
data, GAF_col = readGAF_2(fileName)
allID = set([
".".join([
row[GAF_col.index("Taxon(|taxon)")][6:],
row[GAF_col.index("DB Object Symbol")]
]) for row in data
])
self.update(allID)
#Use a Affymetrix annotation file to define the reference set
elif refType == "AFFY":
f = readFile(fileName)
row = f.readline()
while row[0] == '#':
row = f.readline()
header = row
rd = csv.reader(f)
allID = set()
for row in rd:
#Read gene product id if not control sequence
if ("Control sequence".upper() != row[4].upper()):
allID.add(row[0])
self.update(allID)
else:
print "Sorry, unknown file type !!"
self.extend([])
raise Exception
if len(self) == 0:
logger.handleWarning("No gene products loaded")
except Exception, e:
logger.handleFatal("Unable to read file %s: %s" %
(fileName, str(e)))