def seq_subset_load(infile, subset_mode, subset_args):
"""Load a subset of sequence segments from a sequence file."""
from analysis.sequence_ops import feat_collect, feature_coords, \
coord_chop, get_seq_subset_by_coords
from analysis.seqfile_ops import load_multifasta, surefmt_load, \
write_fasta
from analysis.text_manipulation import adaptive_list_load
if subset_mode is 'flatfile':
# in this case the sequence file MUST be multifasta
try: subset = load_multifasta(infile)
except: raise
else:
print "set of", len(subset), "sequence segments"
subset_file = infile
else:
# load the query single sequence file (convert format if necessary)
try: seq_record = surefmt_load(infile, 'fasta', 'generic_dna')
except: raise
else: print "query sequence loaded from", infile
# load or generate coordinate pairs for target segments
if subset_mode is 'coordinates':
try:
coords_file = subset_args['file']
header = subset_args['header']
columns = subset_args['columns']
coords_list = adaptive_list_load(coords_file, header, columns)
except: raise
else: print len(coords_list), "segments loaded from", infile
elif subset_mode is 'features':
try:
feat_mode = subset_args
features = feat_collect(infile, feat_mode)
coords_list = feature_coords(features)
print coords_list
except: raise
else: print len(coords_list),"features loaded from", infile
elif subset_mode is 'size':
try:
size = subset_args['size']
chop_mode = subset_args['chop_mode']
coords_list = coord_chop(len(seq_record.seq), size, chop_mode)
except: raise
else: print len(coords_list), "segments generated to fit", size
else:
print "ERROR: A mode MUST be specified."
coords_list = None
# collect subset of sequence segments using resulting coords_list
try: subset = get_seq_subset_by_coords(seq_record, coords_list)
except: raise
else: print "subset of", len(subset), "sequence segments"
# save subset to multifasta file for later use or reference
subset_file = seq_record.id+'_subset.fas'
try: write_fasta(subset_file, subset)
except: raise
else: print "subset written to fasta file", subset_file
return subset, subset_file
def test_feat_collect_gene_by_product(self):
self.assertIs(self.count, 1)
feat_mode = {"types": ("gene"), "tags": {"locus_tag": ["locustag 1", "locustag 4"]}}
collected = sequence_ops.feat_collect(self.filename, feat_mode)
self.assertIs(len(collected), 1)
def test_feat_collect_mixed(self):
self.assertIs(self.count, 1)
feat_mode = {"types": ("CDS", "gene"), "tags": {"locus_tag": ("locustag 3"), "product": (("product 2"))}}
collected = sequence_ops.feat_collect(self.filename, feat_mode)
self.assertIs(len(collected), 2)
def test_feat_collect_all_genes(self):
self.assertIs(self.count, 1)
feat_mode = {"types": ("genes"), "tags": {}}
collected = sequence_ops.feat_collect(self.filename, feat_mode)
self.assertIs(len(collected), 2)