def loadPeaksFromFile(self,peaks_file,columns=None):
"""Read peaks data from a file and populate the object
Arguments:
peaks_file (str): the name of the input file to read peaks
data from.
columns (tuple): (optional) tuple with 3 integers
indicating which columns to use from the input
``peaks_file`` for the chromosome, start and end
columns (if not the first three columns). The
columns should be numbered from 1.
"""
# Handle columns
if columns is None:
columns = (1,2,3)
chrom = columns[0] - 1
start = columns[1] - 1
end = columns[2] - 1
ncols = max(chrom,start,end) + 1
# Read in from file
fp = open(peaks_file,'rU')
for line in fp:
# Skip lines that start with a # symbol
if line.startswith('#'):
logging.debug("Peaks file: skipped line: %s" % line.strip())
continue
# Lines are tab-delimited
items = line.strip().split('\t')
if len(items) < ncols:
logging.warning("Peaks file: skipped line: %s" % line.strip())
logging.warning("Insufficient number of fields (%d): need at "
"least %d" % (len(items),ncols))
continue
# Check that items in 'start' and 'end' columns are digits
if not items[start].isdigit() or not items[end].isdigit():
logging.warning("Peaks file: skipped line: %s" % line.strip())
# Indicate problem field(s)
bad_fields = []
for i in (start,end):
if not items[i].isdigit():
bad_fields.append(i)
logging.warning(" %s" % \
make_errline(line,bad_fields))
logging.warning("Expected integer at indicated positions")
continue
# Store in a new Peak object
try:
peak = Peak(items[chrom],
items[start],
items[end])
except PeakRangeError,ex:
logging.error("Peaks file: bad line: %s" % line.strip())
logging.error(" %s" %
make_errline(line,(start,end)))
logging.error("%s" % ex)
raise ex
self.peaks.append(peak)
def loadFeaturesFromFile(self,features_file):
"""Read features from a file and populate the object
Arguments:
features_file: the name of the input file to read features from.
"""
# Local flags etc
line_index = 0
critical_error = False
# Read in data from file
fp = open(features_file,'rU')
for line in fp:
# Increment index
line_index += 1
# Skip lines starting with #
if line.startswith('#'):
logging.debug("Feature file: skipped line: %s" % line.strip())
continue
# Lines are tab-delimited and have at least 5 columns:
# ID chr start end strand
items = line.strip().split('\t')
if len(items) < 5:
logging.warning("Feature file: skipped line: %s" % line.strip())
logging.warning("Insufficient number of fields (%d)" % \
len(items))
continue
# Check line is valid i.e. start and stop should be
# numbers, strand should be + or -
problem_fields = []
if not items[2].isdigit(): problem_fields.append(2)
if not items[3].isdigit(): problem_fields.append(3)
if not (items[4] == '+' or items[4] == '-'): problem_fields.append(4)
if problem_fields:
# If this is the first line then assume it's a header and ignore
if line_index == 1:
logging.warning("%s: first line ignored as header: %s" %
(features_file,line.strip()))
else:
# Indicate problem field(s)
logging.error("%s: critical error line %d: bad values:" %
(features_file,line_index))
logging.error("%s" % line.strip())
logging.error("%s" % make_errline(line.strip(),problem_fields))
# This is a critical error: update flag
critical_error = True
# Continue to next line
continue
elif int(items[2]) >= int(items[3]):
# Start position is same or higher than end
logging.error("%s: critical error line %d: 'end' comes before 'start':" %
(features_file,line_index))
logging.error("%s" % line.strip())
logging.error("%s" % make_errline(line.strip(),(2,3)))
# This is a critical error: update flag but continue reading
critical_error = True
continue
# Store in a new Feature object
feature = Feature(items[0],
items[1],
items[2],
items[3],
items[4],
source_file=features_file)
# Additional flag
if len(items) >= 6:
# Is column 6 a flag?
try:
flag_value = int(items[5])
if flag_value != 0 and flag_value != 1:
flag_value = None
except ValueError:
flag_value = None
# Store value
feature.flag = flag_value
# Store data
self.features.append(feature)
fp.close()
# Deal with postponed critical errors
if critical_error:
raise Exception, "critical error(s) in '%s'" % features_file
# Store the source file
self.source_file = features_file
# Return a reference to this object
return self
def loadPeaksFromFile(self,peaks_file,columns=None,id_column=None):
"""Read peaks data from a file and populate the object
Arguments:
peaks_file (str): the name of the input file to read peaks
data from.
columns (tuple): (optional) tuple with 3 integers
indicating which columns to use from the input
``peaks_file`` for the chromosome, start and end
columns (if not the first three columns). The
columns should be numbered from 1.
id_column (int): (optional) specify a column in the
file which contains the ID for the peak. The
columns are assumed to be numbered from 1.
"""
# Handle columns
if columns is None:
columns = (1,2,3)
chrom = columns[0] - 1
start = columns[1] - 1
end = columns[2] - 1
ncols = max(chrom,start,end) + 1
# Include optional ID column
if id_column is not None:
ncols = max(ncols,id_column)
id_column = id_column - 1
# Read in from file
fp = open(peaks_file,'rU')
for line in fp:
# Skip lines that start with a # symbol
if line.startswith('#'):
logging.debug("Peaks file: skipped line: %s" % line.strip())
continue
# Lines are tab-delimited
items = line.strip().split('\t')
if len(items) < ncols:
logging.warning("Peaks file: skipped line: %s" % line.strip())
logging.warning("Insufficient number of fields (%d): need at "
"least %d" % (len(items),ncols))
continue
# Check that items in 'start' and 'end' columns are digits
if not items[start].isdigit() or not items[end].isdigit():
logging.warning("Peaks file: skipped line: %s" % line.strip())
# Indicate problem field(s)
bad_fields = []
for i in (start,end):
if not items[i].isdigit():
bad_fields.append(i)
logging.warning(" %s" % \
make_errline(line,bad_fields))
logging.warning("Expected integer at indicated positions")
continue
# Optional ID
try:
id_ = items[id_column]
except TypeError:
id_ = None
# Store in a new Peak object
try:
peak = Peak(items[chrom],
items[start],
items[end],
id=id_,
source_file=peaks_file)
except PeakRangeError,ex:
logging.error("Peaks file: bad line: %s" % line.strip())
logging.error(" %s" %
make_errline(line,(start,end)))
logging.error("%s" % ex)
raise ex
self.peaks.append(peak)
def loadFeaturesFromFile(self,features_file):
"""Read features from a file and populate the object
Arguments:
features_file: the name of the input file to read features from.
"""
# Local flags etc
line_index = 0
critical_error = False
# Read in data from file
fp = open(features_file,'rU')
for line in fp:
# Increment index
line_index += 1
# Skip lines starting with #
if line.startswith('#'):
logging.debug("Feature file: skipped line: %s" % line.strip())
continue
# Lines are tab-delimited and have at least 5 columns:
# ID chr start end strand
items = line.strip().split('\t')
if len(items) < 5:
logging.warning("Feature file: skipped line: %s" % line.strip())
logging.warning("Insufficient number of fields (%d)" % \
len(items))
continue
# Check line is valid i.e. start and stop should be
# numbers, strand should be + or -
problem_fields = []
if not items[2].isdigit(): problem_fields.append(2)
if not items[3].isdigit(): problem_fields.append(3)
if not (items[4] == '+' or items[4] == '-'): problem_fields.append(4)
if problem_fields:
# If this is the first line then assume it's a header and ignore
if line_index == 1:
logging.warning("%s: first line ignored as header: %s" %
(features_file,line.strip()))
else:
# Indicate problem field(s)
logging.error("%s: critical error line %d: bad values:" %
(features_file,line_index))
logging.error("%s" % line.strip())
logging.error("%s" % make_errline(line.strip(),problem_fields))
# This is a critical error: update flag
critical_error = True
# Continue to next line
continue
elif int(items[2]) >= int(items[3]):
# Start position is same or higher than end
logging.error("%s: critical error line %d: 'end' comes before 'start':" %
(features_file,line_index))
logging.error("%s" % line.strip())
logging.error("%s" % make_errline(line.strip(),(2,3)))
# This is a critical error: update flag but continue reading
critical_error = True
continue
# Store in a new Feature object
feature = Feature(items[0],
items[1],
items[2],
items[3],
items[4])
# Additional flag
if len(items) >= 6:
# Is column 6 a flag?
try:
flag_value = int(items[5])
if flag_value != 0 and flag_value != 1:
flag_value = None
except ValueError:
flag_value = None
# Store value
feature.flag = flag_value
# Store data
self.features.append(feature)
fp.close()
# Deal with postponed critical errors
if critical_error:
raise Exception, "critical error(s) in '%s'" % features_file
# Return a reference to this object
return self
