def _load_data(self, fp):
"""Internal: populate with data from external file
Arguments
fp: file-like object opened for reading which contains
sample sheet data
"""
section = None
for i, line in enumerate(fp):
line = line.rstrip()
logging.debug(line)
if not line:
# Skip blank lines
continue
if line.startswith('['):
# New section
try:
i = line.index(']')
section = line[1:i]
continue
except ValueError:
logging.error("Bad line (#%d): %s" % (i + 1, line))
if section == 'Header':
# Header lines are comma-separated PARAM,VALUE lines
self._set_param_value(line, self._header)
elif section == 'Reads':
# Read lines are one value per line
value = line.rstrip(',')
if value:
self._reads.append(value)
elif section == 'Settings':
# Settings lines are comma-separated PARAM,VALUE lines
self._set_param_value(line, self._settings)
elif section == 'Data':
# Store data in TabFile object
if self._data is None:
# Initialise TabFile using this first line
# to set the header
self._data = TabFile.TabFile(column_names=line.split(','),
delimiter=',')
else:
self._data.append(tabdata=line)
elif section is None:
raise IlluminaDataError("Not a valid IEM sample sheet?")
else:
raise IlluminaDataError(
"Unrecognised section '%s': not a valid IEM sample sheet?"
% section)
# Clean up data items: remove surrounding whitespace
if self._data is not None:
for line in self._data:
for item in self._data.header():
try:
line[item] = line[item].strip()
except AttributeError:
pass
def annotate_feature_data(gff_lookup,feature_data_file,out_file):
"""Annotate feature data with gene information
Reads in 'feature data' from a tab-delimited input file with feature
IDs in the first column; outputs these data with data about the
parent gene appended to each line.
Arguments:
gff_lookup populated GFFAnnotationLookup instance
feature_data_file input data file with feature IDs in first column
out_file name of output file
"""
# Read the feature data into a TabFile
print "Reading in data from %s" % feature_data_file
feature_data = TabFile.TabFile(filen=feature_data_file,
first_line_is_header=True)
# Append columns for annotation
print "Appending columns for annotation"
for colname in ('exon_parent',
'feature_type_exon_parent',
'gene_ID',
'gene_name',
'chr',
'start',
'end',
'strand',
'gene_length',
'locus',
'description'):
feature_data.appendColumn(colname)
for line in feature_data:
feature_ID = line[0]
annotation = gff_lookup.getAnnotation(feature_ID)
line['exon_parent'] = annotation.parent_feature_name
line['feature_type_exon_parent'] = annotation.parent_feature_type
line['gene_ID'] = annotation.parent_feature_parent
line['gene_name'] = annotation.parent_gene_name
line['chr'] = annotation.chr
line['start'] = annotation.start
line['end'] = annotation.end
line['strand'] = annotation.strand
line['gene_length'] = annotation.gene_length
line['locus'] = annotation.gene_locus
line['description'] = annotation.description
# Output
print "Writing output file %s" % out_file
feature_data.write(out_file,include_header=True,no_hash=True)
def annotate_htseq_count_data(gff_lookup,htseq_files,out_file):
"""Annotate count data from htseq-count output with gene information
Reads in data from one or more htseq-count output files and combines
into a single tab-delimited output file where the counts for each
feature have been appended to data about the parent gene.
Also creates an output 'stats' file which combines the summary data
from the tail of each htseq-count file.
Arguments:
gff_lookup: populated GFFAnnotationLookup instance
htseq_files: list of output files from htseq-count to use as input
out_file: name of output file
"""
# Output files
annotated_counts_out_file = out_file
tables_out_file = \
os.path.join(os.path.dirname(annotated_counts_out_file),
os.path.splitext(os.path.basename(annotated_counts_out_file))[0]+\
"_stats"+os.path.splitext(annotated_counts_out_file)[1])
# Process the HTSeq-count files
print "Processing HTSeq-count files"
htseq_data = {}
for htseqfile in htseq_files:
print "\t%s" % htseqfile
htseq_data[htseqfile] = HTSeqCountFile(htseqfile)
# Create a TabFile for output
print "Building annotated count file for output"
annotated_counts = TabFile.TabFile(column_names=['exon_parent',
'feature_type_exon_parent',
'gene_ID',
'gene_name',
'chr',
'start',
'end',
'strand',
'gene_length',
'locus',
'description'])
for htseqfile in htseq_files:
annotated_counts.appendColumn(htseqfile)
# Combine feature counts and parent feature data
for feature_ID in htseq_data[htseq_files[0]].feature_IDs():
# Get annotation data
annotation = gff_lookup.getAnnotation(feature_ID)
# Build the data line
data = [annotation.parent_feature_name,
annotation.parent_feature_type,
annotation.parent_feature_parent,
annotation.parent_gene_name,
annotation.chr,
annotation.start,
annotation.end,
annotation.strand,
annotation.gene_length,
annotation.gene_locus,
annotation.description]
# Add the counts from each file
for htseqfile in htseq_files:
data.append(htseq_data[htseqfile].count(feature_ID))
# Add to the tabfile
annotated_counts.append(data=data)
# Write the file
print "Writing output file %s" % annotated_counts_out_file
annotated_counts.write(annotated_counts_out_file,include_header=True,no_hash=True)
# Make second file for the trailing table data
print "Building trailing tables data file for output"
table_counts = TabFile.TabFile(column_names=['count'])
for htseqfile in htseq_files:
table_counts.appendColumn(htseqfile)
for name in htseq_data[htseq_files[0]].table():
# Build the data line
data = [name]
for htseqfile in htseq_files:
data.append(htseq_data[htseqfile].table()[name])
table_counts.append(data=data)
print "Writing output file %s" % tables_out_file
table_counts.write(tables_out_file,include_header=True,no_hash=True)
