def __init__(self, file_name, significance=None):
""" Prepares a ResultFileReader to read such from a `file_name`.
If we specify a certain `significance`, we will only consider
those contents with a pvalue less than this `significance`.
"""
self.file = IndexedReadOnlyFile(file_name, r"^\w+")
self.keys = self.file.get_keys()
self.pval_regex = re.compile(r"^\d")
self.go_names = dict()
if significance is not None:
self.alpha = significance
else:
self.alpha = 1000.0
def __init__(self, file_name, significance=None):
""" Prepares a ResultFileReader to read such from a `file_name`.
If we specify a certain `significance`, we will only consider
those contents with a pvalue less than this `significance`.
"""
self.file = IndexedReadOnlyFile(file_name, "^\w+")
self.keys = self.file.get_keys()
self.pval_regex = re.compile("^\d")
self.go_names = dict()
if significance is not None:
self.alpha = significance
else:
self.alpha = 1000.0
class ResultFileReader(object):
"""Class implementing a parser of the
GFam result file, i.e., a text file with the
following format:
protein_id
p-value: GO:XXXXXXX (function)
p-value: GO:XXXXXXX (function)
...
protein_id2
p-value: ...
...
"""
def __init__(self, file_name, significance=None):
""" Prepares a ResultFileReader to read such from a `file_name`.
If we specify a certain `significance`, we will only consider
those contents with a pvalue less than this `significance`.
"""
self.file = IndexedReadOnlyFile(file_name, "^\w+")
self.keys = self.file.get_keys()
self.pval_regex = re.compile("^\d")
self.go_names = dict()
if significance is not None:
self.alpha = significance
else:
self.alpha = 1000.0
def get_keys(self):
""" Return the set of protein-ids of the file
"""
return self.keys
def get_result_as_dict(self):
""" Retrieves the whole dataset as a dictionary.
Not recommended if the file is too large.
"""
d = dict()
for key in self.keys:
d[key] = self.__getitem__(key)
return d
def __getitem__(self, key):
""" Gets the set of GO terms and p-values for a
certain key (which should be a real key in
the file).
"""
list_go_terms = []
for line in [l for l in self.file[key] if self.pval_regex.match(l)]:
pvalue, goterm = line.split(' ',2)[0:2]
pvalue = float(pvalue[0:-1])
if pvalue < self.alpha:
list_go_terms.append((goterm, pvalue))
if goterm not in self.go_names:
name = line.split('(', 1)[1][0:-1]
self.go_names[goterm] = name
return list_go_terms
def get_go_names(self):
if not self.go_names:
for key in self.keys:
self.__getitem__(key)
return self.go_names
class ResultFileReader(object):
"""Class implementing a parser of the
GFam result file, i.e., a text file with the
following format:
protein_id
p-value: GO:XXXXXXX (function)
p-value: GO:XXXXXXX (function)
...
protein_id2
p-value: ...
...
"""
def __init__(self, file_name, significance=None):
""" Prepares a ResultFileReader to read such from a `file_name`.
If we specify a certain `significance`, we will only consider
those contents with a pvalue less than this `significance`.
"""
self.file = IndexedReadOnlyFile(file_name, r"^\w+")
self.keys = self.file.get_keys()
self.pval_regex = re.compile(r"^\d")
self.go_names = dict()
if significance is not None:
self.alpha = significance
else:
self.alpha = 1000.0
def get_keys(self):
""" Return the set of protein-ids of the file
"""
return self.keys
def get_result_as_dict(self):
""" Retrieves the whole dataset as a dictionary.
Not recommended if the file is too large.
"""
results = dict()
for key in self.keys:
results[key] = self.__getitem__(key)
return results
def __getitem__(self, key):
""" Gets the set of GO terms and p-values for a
certain key (which should be a real key in
the file).
"""
list_go_terms = []
for line in [l for l in self.file[key] if self.pval_regex.match(l)]:
pvalue, goterm = line.split(' ', 2)[0:2]
pvalue = float(pvalue[0:-1])
if pvalue < self.alpha:
list_go_terms.append((goterm, pvalue))
if goterm not in self.go_names:
name = line.split('(', 1)[1][0:-1]
self.go_names[goterm] = name
return list_go_terms
def get_go_names(self):
if not self.go_names:
for key in self.keys:
self.__getitem__(key)
return self.go_names
