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test_prodigal.py
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test_prodigal.py
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import tempfile
import os
import filecmp
import csv
import shutil
import nose
import yaml
from Bio import SeqIO
import vica
with open(vica.CONFIG_PATH) as cf:
config = yaml.safe_load(cf)
codon_list = config["prodigal"]["codon_list"]
def test_clr():
composition =[1, 4, 7, 9, 10, 0, 1]
result = [0.27108151858446849, 1.084326074337874, 1.8975706300912796,
2.4397336672602168, 2.7108151858446852, 0.0, 0.27108151858446849]
for i, val in enumerate(result):
nose.tools.assert_almost_equal(vica.prodigal.clr(composition)[i], val)
def test_ilr():
composition =[1, 4, 7, 9, 10, 0, 1]
result = [-0.57505074013627433, -0.99601709884611478, -1.1738174079530661,
-1.1516977356976139, 1.5342671140651829, 1.0457196607598642]
for i, val in enumerate(result):
nose.tools.assert_almost_equal(vica.prodigal.ilr(composition)[i], val)
def test_call_genes():
td = tempfile.mkdtemp()
outfile1 = os.path.join(td,"genes.fasta")
vica.prodigal._call_genes(infile="tests/test-data/2testseqs.fasta",
outfile=outfile1)
nose.tools.ok_(filecmp.cmp("tests/test-data/calledgenes.fasta", outfile1, shallow=False))
shutil.rmtree(td)
def test_gene_to_codon():
genestring = 'ATCGATCGCATCGACTAGCCACGTACGACGACTGACGTCG'
genedict = ['ATC', 'GAT', 'CGC', 'ATC', 'GAC', 'TAG', 'CCA', 'CGT', 'ACG',
'ACG', 'ACT', 'GAC', 'GTC']
result = vica.prodigal._gene_to_codon(genestring)
nose.tools.eq_(result, genedict)
def test_codon_to_dict():
genestring = 'ATCGATCGCATCGACTAGCCACGTACGACGACTGACGTCG'
d0 = {'CGT': 1, 'GAT': 1, 'ATC': 2, 'ACT': 1, 'ACG': 2, 'GAC': 2, 'GTC': 1, 'CGC': 1, 'CCA': 1, 'TAG': 1}
d1 = {'ACG': 1, 'CAC': 1, 'GTA': 1, 'GCA': 1, 'AGC': 1, 'TCG': 3, 'CTG': 1, 'ACT': 1, 'ATC': 1, 'CGA': 2}
d2 = {'TCG': 1, 'CGA': 2, 'CGT': 1, 'GCC': 1, 'CTA': 1, 'GAC': 2, 'TGA': 1, 'CAT': 1, 'ACG': 1, 'TAC': 1}
r0 = vica.prodigal._codon_to_dict(genestring, 0)
r1 = vica.prodigal._codon_to_dict(genestring, 1)
r2 = vica.prodigal._codon_to_dict(genestring, 2)
nose.tools.eq_(r0, d0)
nose.tools.eq_(r1, d1)
nose.tools.eq_(r2, d2, msg="{} did not mactch expected value of {}".format(r2, d2))
def _parse_prodigal_id_from_biopython():
stripped_id = '>NC_000'
result = vica.prodigal._parse_prodigal_id_from_biopython('>NC_000_001')
nose.tools.eq_(result, stripped_id)
def almost_equal(value_1, value_2, accuracy = 10**-8):
'''a Function to compare tuples of float values'''
return abs(value_1 - value_2) < accuracy
def test_count_dict_to_clr_array():
d0 = {'CGT': 1, 'GAT': 1, 'ATC': 2, 'ACT': 1, 'ACG': 2, 'GAC': 2, 'GTC': 1,
'CGC': 1, 'CCA': 1, 'TAG': 1}
expected = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.81225239635623547, 0.0, 0.0, 0.0, 0.0, 0.81225239635623547, 0.0, 0.0, 0.0, 0.81225239635623547, 0.0, 0.81225239635623547, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.81225239635623547, 0.0, 0.0, 1.6245047927124709, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.6245047927124709, 0.0, 0.0, 0.0, 0.0, 0.81225239635623547, 0.0, 0.81225239635623547, 0.0, 1.6245047927124709, 0.0, 0.0, 0.0, 0.0, 0.0]
result = vica.prodigal.count_dict_to_clr_array(d0, codon_list)
nose.tools.ok_(all(almost_equal(*values) for values in zip(expected, result)))
def test_count_dict_to_ilr_array():
d0 = {'CGT': 1, 'GAT': 1, 'ATC': 2, 'ACT': 1, 'ACG': 2, 'GAC': 2, 'GTC': 1,
'CGC': 1, 'CCA': 1, 'TAG': 1}
expected = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.78471036590622656, 0.052430666733412762, 0.049250035659379708, 0.046433378917902231, 0.043921579351258642, -0.75001803758170915, 0.079267717285667116, 0.075578802966779754, 0.072218046827921739, -0.72600691487382352, 0.099480195671282773, -0.70090152321249855, 0.12262596457641053, 0.11816533618132451, 0.11401788429298802, 0.11015174113954165, 0.10653922134156935, 0.10315615749345099, 0.09998135851902494, -0.70322219713140899, 0.11773010326165942, 0.11441309478231763, -1.4911237639366819, 0.15163392649017504, 0.14769470968813433, 0.14395499611465096, 0.14040000307035622, 0.13701637323833493, 0.13379200691796261, 0.13071591741042154, 0.12777810591205632, -1.4817806559659221, 0.15721923036048868, 0.15390898109601467, 0.15073525918484715, 0.14768978849961878, -0.65948476591381477, 0.15772634569942362, -0.64983138856456379, 0.16701245952274074, -1.4457210713825195, 0.19026503939080927, 0.18689725044635552, 0.1836466155121933, 0.18050712578909411, 0.17747317650455946]
result = vica.prodigal.count_dict_to_ilr_array(d0, codon_list)
nose.tools.ok_(all(almost_equal(*values) for values in zip(expected, result)))
def test_dsum():
d0 = {'CGT': 1, 'GAT': 1, 'ATC': 2, 'ACT': 1, 'ACG': 2, 'GAC': 2, 'GTC': 1,
'CGC': 1, 'CCA': 1, 'TAG': 1}
d1 = {'ACG': 1, 'CAC': 1, 'GTA': 1, 'GCA': 1, 'AGC': 1, 'TCG': 3, 'CTG': 1,
'ACT': 1, 'ATC': 1, 'CGA': 2}
expected = {'CGT': 1, 'GTA': 1, 'CCA': 1, 'ACT': 2, 'AGC': 1, 'TAG': 1,
'CGA': 2, 'TCG': 3, 'GCA': 1, 'CGC': 1, 'ATC': 3, 'GAT': 1,
'GTC': 1, 'CAC': 1, 'ACG': 3, 'GAC': 2, 'CTG': 1}
result = vica.prodigal.dsum(d0, d1)
nose.tools.eq_(result, expected)
def test_count_codon_in_gene():
testfasta = 'tests/test-data/2testseqs.fasta'
expected = {0: {'GAC': 53, 'TAC': 11, 'AGA': 18, 'CAG': 56, 'CGT': 29,
'ACC': 49, 'ATG': 46, 'GCC': 93, 'AAC': 33, 'AAA': 34,
'ATT': 28, 'GCA': 46, 'TAT': 22, 'GAG': 41, 'TCC': 33,
'GCG': 95, 'GAA': 49, 'GTG': 51, 'CAC': 17, 'TCG': 79,
'CGG': 51, 'ACG': 38, 'TTC': 42, 'TGG': 27, 'TGT': 14,
'ACT': 14, 'TGA': 18, 'CTG': 55, 'GCT': 30, 'AAG': 34,
'GTT': 31, 'CCA': 34, 'CAT': 29, 'CAA': 27, 'CTA': 8,
'TTT': 23, 'GGA': 36, 'GTA': 10, 'GGG': 53, 'TCA': 25,
'GAT': 48, 'TGC': 36, 'CTC': 22, 'ACA': 18, 'CCT': 16,
'CTT': 25, 'CCC': 41, 'CCG': 75, 'GGC': 63, 'TAA': 5,
'GGT': 43, 'CGA': 38, 'TCT': 25, 'AGG': 36, 'CGC': 78,
'ATC': 85, 'AAT': 19, 'GTC': 44, 'TTG': 44, 'ATA': 9,
'AGT': 13, 'AGC': 51, 'TAG': 13, 'TTA': 4},
1: {'CTT': 21, 'GAC': 31, 'TAC': 8, 'AGA': 45, 'CAG': 35,
'CGT': 35, 'ACC': 33, 'ATG': 44, 'GCC': 54, 'AAC': 38,
'CGA': 63, 'ATT': 17, 'GCA': 51, 'TAT': 8, 'GAG': 16,
'TCC': 35, 'GCG': 94, 'GAA': 36, 'TGA': 49, 'ACT': 17,
'CAC': 22, 'TCG': 67, 'CGG': 93, 'ACA': 23, 'TTC': 22,
'TGG': 64, 'TCA': 65, 'AGC': 36, 'GTG': 35, 'CTG': 43,
'CCC': 34, 'AAG': 29, 'GTT': 29, 'CCA': 57, 'CAT': 29,
'AAT': 19, 'CTA': 8, 'TTT': 27, 'GGA': 28, 'GTA': 12,
'GGG': 40, 'GCT': 29, 'GAT': 27, 'TGC': 50, 'CCT': 57,
'CTC': 13, 'CCG': 68, 'GGC': 59, 'TAA': 7, 'GGT': 40,
'AAA': 29, 'TCT': 26, 'AGG': 56, 'CGC': 96, 'ATC': 47,
'ACG': 41, 'GTC': 23, 'TGT': 33, 'TTG': 53, 'ATA': 10,
'AGT': 7, 'TAG': 8, 'CAA': 37, 'TTA': 5},
2: {'GAC': 42, 'AGA': 22, 'CAG': 67, 'CGC': 68, 'CAA': 41,
'ATG': 16, 'GCC': 80, 'TGT': 34, 'CGA': 85, 'ATT': 15,
'GCA': 39, 'TAT': 13, 'GAG': 20, 'TCC': 23, 'GCG': 80,
'GAA': 38, 'TGA': 44, 'CAC': 39, 'TCG': 33, 'CGG': 80,
'ACA': 25, 'TTC': 45, 'TGG': 35, 'TCA': 28, 'ACT': 16,
'GTG': 17, 'CTG': 41, 'CCC': 35, 'TAA': 5, 'GTT': 38,
'CCA': 37, 'CAT': 49, 'ACC': 28, 'CTA': 14, 'TTT': 22,
'GGA': 40, 'GTA': 14, 'AGG': 25, 'GGG': 55, 'AGT': 6,
'GAT': 85, 'TGC': 62, 'CTC': 36, 'CCT': 31, 'CTT': 38,
'AAC': 31, 'CCG': 53, 'GGC': 99, 'GGT': 58, 'AAA': 36,
'TCT': 21, 'TAC': 7, 'CGT': 37, 'ATC': 35, 'AAT': 21,
'TTG': 21, 'GTC': 46, 'GCT': 42, 'ATA': 17, 'AGC': 35,
'TAG': 10, 'AAG': 21, 'TTA': 6, 'ACG': 30}}
records = SeqIO.parse(testfasta, 'fasta')
record = next(records)
result = vica.prodigal.count_codon_in_gene(record)
nose.tools.eq_(result, expected)
def test_count_codons():
dt = tempfile.mkdtemp()
print(dt)
outfile = os.path.join(dt, "codons.csv")
expected = 'tests/test-data/codons.csv'
genefile = 'tests/test-data/calledgenes.fasta'
seqs = SeqIO.parse(genefile, 'fasta')
with open(outfile, 'w') as csvfile:
csv_writer_instance = csv.writer(csvfile, lineterminator='\n')
vica.prodigal.count_codons(seqio_iterator= seqs, csv_writer_instance=csv_writer_instance, codon_list=codon_list)
nose.tools.ok_(filecmp.cmp(expected, outfile, shallow=False))
shutil.rmtree(dt)
def test_contigs_to_feature_file():
infile = "tests/test-data/2testseqs.fasta"
dt = tempfile.mkdtemp()
outfile = os.path.join(dt, "codons.csv")
expected = 'tests/test-data/codons.csv'
vica.prodigal.contigs_to_feature_file(infile=infile, outfile=outfile, dtemp=dt, codon_list=codon_list)
nose.tools.ok_(filecmp.cmp(expected, outfile, shallow=False))
shutil.rmtree(dt)