def to_sam(self, fasta):
"""
Prints items as SAM lines
"""
s = []
genome = GFFutils.Genome(fasta)
for item in self.items:
s.append(item.to_sam(genome))
return ''.join(s)
def to_fastq(self, fasta):
"""
Creates sequences and fake quality scores. Sequence names are the same
as the GFFFeature.id.
"""
genome = GFFutils.Genome(fasta)
s = []
for item in self.items:
s.append(item.to_fastq(genome))
return ''.join(s)
g10.parse(gene_models4)
gene_models5 = gene_models5.splitlines(True)
g11 = GenomeModel(chrom_start=1, scalar=5, read_length=3, debug=False)
g11.parse(gene_models5)
gene_models6 = gene_models6.splitlines(True)
g12 = GenomeModel(chrom='chr3R',
chrom_start=101,
scalar=5,
read_length=3,
debug=False)
g12.parse(gene_models6)
here = os.path.dirname(__file__)
genome = GFFutils.Genome(os.path.join(here, 'data/dm3.chr2L.oneline.fa'))
def feature_exists(genome_model_obj,
start,
stop,
featuretype,
chrom='chr2L',
strand='+'):
# Checks to see if a feature exists. Does not check names, only genomic
# coords and featuretype
for feature in genome_model_obj.features:
if (feature.start == start) and (feature.stop == stop) \
and (feature.chrom == chrom) and (feature.strand == strand) \
and (feature.featuretype == featuretype):
return True
