def setUpClass(cls):
# Example of crc64 collision from Sebastian Bassi using the
# immunoglobulin lambda light chain variable region from H**o sapiens
# Both sequences share the same CRC64 checksum: 44CAAD88706CC153
cls.str_light_chain_one = (
"QSALTQPASVSGSPGQSITISCTGTSSDVGSYNLVSWYQQHPGKAPKLMIYEGSKRPSGV"
"SNRFSGSKSGNTASLTISGLQAEDEADYYCSSYAGSSTLVFGGGTKLTVL")
cls.str_light_chain_two = (
"QSALTQPASVSGSPGQSITISCTGTSSDVGSYNLVSWYQQHPGKAPKLMIYEGSKRPSGV"
"SNRFSGSKSGNTASLTISGLQAEDEADYYCCSYAGSSTWVFGGGTKLTVL")
X = CodonAdaptationIndex()
path = os.path.join("CodonUsage", "HighlyExpressedGenes.txt")
X.generate_index(path)
cls.X = X
def test_codon_usage_custom(self):
"""Test Codon Adaptation Index (CAI) using FASTA file for background."""
# We need a FASTA file of CDS sequences to count the codon usage...
dna_fasta_filename = "fasta.tmp"
dna_genbank_filename = "GenBank/NC_005816.gb"
record = SeqIO.read(dna_genbank_filename, "genbank")
records = []
for feature in record.features:
if feature.type == "CDS" and len(feature.location.parts) == 1:
start = feature.location.start.position
end = feature.location.end.position
table = int(feature.qualifiers["transl_table"][0])
if feature.strand == -1:
seq = record.seq[start:end].reverse_complement()
else:
seq = record.seq[start:end]
# Double check we have the CDS sequence expected
# TODO - Use any cds_start option if/when added to deal with the met
a = "M" + str(seq[3:].translate(table))
b = feature.qualifiers["translation"][0] + "*"
self.assertEqual(a, b, "%r vs %r" % (a, b))
records.append(
SeqRecord(
seq,
id=feature.qualifiers["protein_id"][0],
description=feature.qualifiers["product"][0],
)
)
with open(dna_fasta_filename, "w") as handle:
SeqIO.write(records, handle, "fasta")
CAI = CodonAdaptationIndex()
# Note - this needs a FASTA file which containing non-ambiguous DNA coding
# sequences - which should each be a whole number of codons.
CAI.generate_index(dna_fasta_filename)
# Now check codon usage index (CAI) using this species
self.assertEqual(
record.annotations["source"], "Yersinia pestis biovar Microtus str. 91001"
)
value = CAI.cai_for_gene("ATGCGTATCGATCGCGATACGATTAGGCGGATG")
self.assertAlmostEqual(value, 0.67213, places=5)
os.remove(dna_fasta_filename)
def test_codon_usage_custom(self):
"""Test Codon Adaptation Index (CAI) using FASTA file for background."""
#We need a FASTA file of CDS sequences to count the codon usage...
dna_fasta_filename = "fasta.tmp"
dna_genbank_filename = "GenBank/NC_005816.gb"
record = SeqIO.read(dna_genbank_filename, "genbank")
records = []
for feature in record.features:
if feature.type == "CDS" and not feature.sub_features:
start = feature.location.start.position
end = feature.location.end.position
table = int(feature.qualifiers["transl_table"][0])
if feature.strand == -1:
seq = record.seq[start:end].reverse_complement()
else:
seq = record.seq[start:end]
#Double check we have the CDS sequence expected
#TODO - Use any cds_start option if/when added to deal with the met
a = "M" + str(seq[3:].translate(table))
b = feature.qualifiers["translation"][0] + "*"
self.assertEqual(a, b, "%r vs %r" % (a, b))
records.append(SeqRecord(seq, id=feature.qualifiers["protein_id"][0],
description=feature.qualifiers["product"][0]))
with open(dna_fasta_filename, "w") as handle:
SeqIO.write(records, handle, "fasta")
CAI = CodonAdaptationIndex()
# Note - this needs a FASTA file which containing non-ambiguous DNA coding
# sequences - which should each be a whole number of codons.
CAI.generate_index(dna_fasta_filename)
# Now check codon usage index (CAI) using this species
self.assertEqual(record.annotations["source"],
"Yersinia pestis biovar Microtus str. 91001")
self.assertEqual("%0.5f" % CAI.cai_for_gene("ATGCGTATCGATCGCGATACGATTAGGCGGATG"),
"0.67213")
os.remove(dna_fasta_filename)
#TODO - Use any cds_start option if/when added to deal with the met
assert "M" + str(seq[3:].translate(table)) \
== feature.qualifiers["translation"][0]+"*"
records.append(SeqRecord(seq, id=feature.qualifiers["protein_id"][0],
description=feature.qualifiers["product"][0]))
del start, end, table, seq
if os.path.isfile(dna_fasta_filename):
os.remove(dna_fasta_filename)
handle = open(dna_fasta_filename, "w")
SeqIO.write(records, handle, "fasta")
handle.close()
CAI = CodonAdaptationIndex()
# Note - this needs a FASTA file which containing non-ambiguous DNA coding
# sequences - which should each be a whole number of codons.
CAI.generate_index(dna_fasta_filename)
print "Example CAI %0.5f using %s" \
% (CAI.cai_for_gene("ATGCGTATCGATCGCGATACGATTAGGCGGATG"),
record.annotations["source"])
os.remove(dna_fasta_filename)
del record, records
del dna_genbank_filename
del dna_fasta_filename
print
###################
# crc64 collision #
###################
#TODO - Use any cds_start option if/when added to deal with the met
assert "M" + str(seq[3:].translate(table)) \
== feature.qualifiers["translation"][0]+"*"
records.append(SeqRecord(seq, id=feature.qualifiers["protein_id"][0],
description=feature.qualifiers["product"][0]))
del start, end, table, seq
if os.path.isfile(dna_fasta_filename) :
os.remove(dna_fasta_filename)
handle = open(dna_fasta_filename, "w")
SeqIO.write(records, handle, "fasta")
handle.close()
CAI = CodonAdaptationIndex()
# Note - this needs a FASTA file which containing non-ambiguous DNA coding
# sequences - which should each be a whole number of codons.
CAI.generate_index(dna_fasta_filename)
print "Example CAI %0.5f using %s" \
% (CAI.cai_for_gene("ATGCGTATCGATCGCGATACGATTAGGCGGATG"),
record.annotations["source"])
os.remove(dna_fasta_filename)
del record, records
del dna_genbank_filename
del dna_fasta_filename
print
###################
# crc64 collision #
###################
