class Example(object):
tss_dict = [{"seq_id": "aaa", "source": "Refseq",
"feature": "TSS", "start": 3,
"end": 3, "phase": ".", "strand": "+", "score": "."},
{"seq_id": "aaa", "source": "Refseq",
"feature": "TSS", "start": 16,
"end": 16, "phase": ".", "strand": "-", "score": "."},
{"seq_id": "aaa", "source": "Refseq",
"feature": "TSS", "start": 54,
"end": 54, "phase": ".", "strand": "+", "score": "."}]
attributes_tss = [{"ID": "CDS0", "Name": "CDS_0", "type": "Primary",
"associated_gene": "AAA_00001",
"utr_length": "Primary_25"},
{"ID": "CDS1", "Name": "CDS_1", "type": "Internal",
"associated_gene": "AAA_00002",
"utr_length": "Internal_NA"},
{"ID": "CDS2", "Name": "CDS_2",
"type": "Primary,Antisense",
"associated_gene": "AAA_00004,AAA_00006",
"utr_length": "Primary_25,Internal_NA"}]
tss2_dict = [
{"seq_id": "aaa", "source": "Refseq", "feature": "TSS", "start": 3,
"end": 3, "phase": ".", "strand": "+", "score": "."},
{"seq_id": "aaa", "source": "Refseq", "feature": "TSS", "start": 18,
"end": 18, "phase": ".", "strand": "-", "score": "."},
{"seq_id": "aaa", "source": "Refseq", "feature": "TSS", "start": 23,
"end": 23, "phase": ".", "strand": "+", "score": "."}]
attributes_tss2 = [{"ID": "CDS0", "Name": "CDS_0", "type": "Primary",
"associated_gene": "AAA_00001",
"utr_length": "Primary_25"},
{"ID": "CDS1", "Name": "CDS_1", "type": "Internal",
"associated_gene": "AAA_00002",
"utr_length": "Internal_NA"},
{"ID": "CDS2", "Name": "CDS_2",
"type": "Primary,Antisense",
"associated_gene": "AAA_00004,AAA_00006",
"utr_length": "Primary_25,Internal_NA"}]
gff_dict = [{"start": 6, "end": 15, "phase": ".",
"strand": "+", "seq_id": "aaa", "score": ".",
"source": "Refseq", "feature": "gene"},
{"start": 1258, "end": 2234, "phase": ".",
"strand": "+", "seq_id": "aaa", "score": ".",
"source": "Refseq", "feature": "gene"},
{"start": 3544, "end": 6517, "phase": ".",
"strand": "-", "seq_id": "aaa", "score": ".",
"source": "Refseq", "feature": "gene"}]
attributes_gff = [
{"ID": "gene0", "Name": "gene_0", "locus_tag": "AAA_00001"},
{"ID": "gene0", "Name": "gene_1", "locus_tag": "AAA_00002"},
{"ID": "gene1", "Name": "gene_2", "locus_tag": "AAA_00003"}]
tsss = []
tsss2 = []
genes = []
for index in range(0, 3):
tsss.append(Create_generator(
tss_dict[index], attributes_tss[index], "gff"))
tsss2.append(Create_generator(
tss2_dict[index], attributes_tss2[index], "gff"))
genes.append(Create_generator(
gff_dict[index], attributes_gff[index], "gff"))
def test_check_overlap(self):
tss_m_dict = {"seq_id": "aaa", "source": "Refseq", "feature": "TSS", "start": 7,
"end": 7, "phase": ".", "strand": "+", "score": "."}
attributes_tss_m = {"ID": "TSS0", "Name": "TSS_0", "type": "Primary,Internal",
"associated_gene": "AAA_00001,AAA_00004", "UTR_length": "Primary_25,Internal_NA"}
tss_m = Create_generator(tss_m_dict, attributes_tss_m, "gff")
tss_p_dict = {"seq_id": "aaa", "source": "Refseq", "feature": "TSS", "start": 7,
"end": 7, "phase": ".", "strand": "+", "score": "."}
attributes_tss_p = {"ID": "TSS0", "Name": "TSS_0", "type": "Primary,Internal",
"associated_gene": "AAA_00001,AAA_00004", "UTR_length": "Primary_25,Internal_NA"}
tss_p = Create_generator(tss_p_dict, attributes_tss_p, "gff")
tss_pre_dict = {"seq_id": "aaa", "source": "Refseq", "feature": "TSS", "start": 3,
"end": 3, "phase": ".", "strand": "+", "score": "."}
attributes_tss_pre = {"ID": "TSS0", "Name": "TSS_0", "type": "Primary,Internal",
"associated_gene": "AAA_00001,AAA_00004", "UTR_length": "Primary_25,Internal_NA"}
tss_pre = Create_generator(tss_pre_dict, attributes_tss_pre, "gff")
nums = {"tss_p": 0, "tss_m": 0, "tss": 0}
tsss = {"tsss_p":[], "tsss_m": [], "merge": []}
num_strain = {"aaa": {"overlap": 0, "tsspredator": 0, "manual": 0}}
overlap_num = 0
output = mm.check_overlap(True, tss_pre, nums, False, num_strain, overlap_num,
tss_m, tss_p, tsss, 1000, self.example.genes, self.example.genes)
self.assertEqual(output, (False, 3, 1))
output = mm.check_overlap(False, tss_pre, nums, 100, num_strain, overlap_num,
tss_m, tss_p, tsss, 1000, self.example.genes, self.example.genes)
self.assertEqual(output, (False, 1000, 0))
class Example(object):
gff_file = """test RefSeq CDS 5 10 . + . ID=cds0;Name=CDS_0"""
tss_file = """test RefSeq TSS 3 3 . + . ID=tss0;Name=TSS_0"""
tss_dict = [{
"seq_id": "test",
"source": "intergenic",
"feature": "TSS",
"start": 170,
"end": 170,
"phase": ".",
"strand": "+",
"score": "."
}]
attributes_tsss = [{"ID": "tss0", "Name": "TSS_0"}]
tsss = []
tsss.append(Create_generator(tss_dict[0], attributes_tsss[0], "gff"))
gff_dict = [{
"seq_id": "test",
"source": "RefSeq",
"feature": "CDS",
"start": 200,
"end": 270,
"phase": ".",
"strand": "+",
"score": "."
}]
attributes_gff = [{"ID": "cds0", "Name": "CDS_0"}]
gffs = []
gffs.append(Create_generator(gff_dict[0], attributes_gff[0], "gff"))
out_stat_test = """All genomes:
The number of cds which is start from TSS: 250 (0.4166666666666667)
The number of tRNA which is start from TSS: 20 (0.6666666666666666)
The number of rRNA which is start from TSS: 20 (0.6666666666666666)"""
out_stat = """All genomes:
def test_compare(self):
data1_dict = {"seq_id": "aaa", "source": "Refseq", "feature": "transcript", "start": 140,
"end": 367, "phase": ".", "strand": "+", "score": "."}
data2_dict = {"seq_id": "aaa", "source": "Refseq", "feature": "transcript", "start": 180,
"end": 400, "phase": ".", "strand": "+", "score": "."}
data3_dict = {"seq_id": "aaa", "source": "Refseq", "feature": "transcript", "start": 50,
"end": 138, "phase": ".", "strand": "+", "score": "."}
data4_dict = {"seq_id": "aaa", "source": "Refseq", "feature": "transcript", "start": 5650,
"end": 7100, "phase": ".", "strand": "+", "score": "."}
attributes = {"ID": "tran0", "Name": "Tran_0", "locus_tag": "AAA_00001"}
overlap = False
data1 = Create_generator(data1_dict, attributes, "gff")
data2 = Create_generator(data2_dict, attributes, "gff")
data3 = Create_generator(data3_dict, attributes, "gff")
data4 = Create_generator(data4_dict, attributes, "gff")
overlap12 = cft.compare(data1, data2, overlap, 5)
self.assertEqual(data1.start, 140)
self.assertEqual(data1.end, 400)
overlap13 = cft.compare(data1, data3, overlap, 5)
self.assertEqual(data1.start, 50)
self.assertEqual(data1.end, 400)
overlap14 = cft.compare(data1, data4, overlap, 5)
self.assertEqual(data1.start, 50)
self.assertEqual(data1.end, 400)
self.assertTrue(overlap12)
self.assertTrue(overlap13)
self.assertFalse(overlap14)
def test_sub_operon(self):
tss_dict = [{"seq_id": "aaa", "source": "Refseq",
"feature": "TSS", "start": 140,
"end": 140, "phase": ".", "strand": "+", "score": "."},
{"seq_id": "aaa", "source": "Refseq",
"feature": "TSS", "start": 200,
"end": 200, "phase": ".", "strand": "+", "score": "."}]
attributes_tss = [
{"ID": "tss0", "Name": "TSS_0", "locus_tag": "AAA_00001"},
{"ID": "tss1", "Name": "TSS_1", "locus_tag": "BBB_00001"}]
gff_dict = [{"seq_id": "aaa", "source": "Refseq",
"feature": "CDS", "start": 540,
"end": 640, "phase": ".", "strand": "+", "score": "."},
{"seq_id": "aaa", "source": "Refseq",
"feature": "TSS", "start": 166,
"end": 198, "phase": ".", "strand": "+", "score": "."}]
attributes_gff = [
{"ID": "tss0", "Name": "TSS_0", "locus_tag": "AAA_00001"},
{"ID": "tss1", "Name": "TSS_1", "locus_tag": "BBB_00001"}]
tsss = {"with_feature": True, "num_feature": 2, "data_list": []}
genes = {"data_list": []}
for index in range(0, 2):
genes["data_list"].append(Create_generator(
gff_dict[index], attributes_gff[index], "gff"))
tsss["data_list"].append(Create_generator(
tss_dict[index], attributes_tss[index], "gff"))
operons = op.sub_operon("+", tsss, 141, 800, genes, 30)
self.assertDictEqual(operons[0],
{'end': 199, 'start': 141, 'strand': '+'})
self.assertDictEqual(operons[1],
{'end': 799, 'start': 200, 'strand': '+'})
class Example(object):
inter = """aaa UTR_derived sORF 2 6 . + . ID=inter0;Name=inter_00000;UTR_type=3utr"""
srna = """aaa UTR_derived sRNA 5 8 . + . ID=aaa_srna0;Name=srna_00000;UTR_type=3utr"""
tss = """aaa tsspredator TSS 1 1 . + . ID=aaa_tss0;Name=TSS_00000"""
wigs = {"aaa": {"frag_1": {"track_1|+|frag": [
100, 30, 23, 21, 21, 2, 100, 30, 23, 21, 21,
2, 100, 30, 23, 21, 21, 2, 100, 30, 23, 21, 21, 2]}}}
ta_dict = [{"seq_id": "aaa", "source": "intergenic",
"feature": "Transcript", "start": 1,
"end": 23, "phase": ".", "strand": "+", "score": "."}]
attributes_tas = [{"ID": "tran0", "Name": "Transcript_0"}]
tas = []
tas.append(Create_generator(ta_dict[0], attributes_tas[0], "gff"))
tss_dict = [{"seq_id": "aaa", "source": "tsspredator",
"feature": "TSS", "start": 1,
"end": 1, "phase": ".", "strand": "+", "score": "."}]
attributes_tss = [{"ID": "tss0", "Name": "TSS_0"}]
tsss = []
tsss.append(Create_generator(tss_dict[0], attributes_tss[0], "gff"))
srna_dict = [{"seq_id": "aaa", "source": "Refseq",
"feature": "sRNA", "start": 5,
"end": 8, "phase": ".", "strand": "+", "score": "."}]
attributes_srna = [{"ID": "srna0", "Name": "sRNA_0"}]
srnas = []
srnas.append(Create_generator(srna_dict[0], attributes_srna[0], "gff"))
def test_diff_strand_tss_gene(self):
tss_dict = {"seq_id": "aaa", "source": "Refseq",
"feature": "TSS", "start": 3,
"end": 3, "phase": ".", "strand": "+", "score": "."}
attributes_tss = {"ID": "TSS0", "Name": "TSS_0",
"type": "Primary,Internal",
"associated_gene": "AAA_00001,AAA_00004",
"utr_length": "Primary_25,Internal_NA"}
tss = Create_generator(tss_dict, attributes_tss, "gff")
tss_entry = [tss.attribute_string, {
"utr_length": "Primary_25", "type": "Primary",
"associated_gene": "AAA_00001"}]
anti_ends = {"forward": 1, "reverse": -1}
gene_ends = {"forward": -1, "reverse": -1}
gff_dict = {"seq_id": "aaa", "source": "Refseq",
"feature": "CDS", "start": 6,
"end": 12, "phase": ".", "strand": "-", "score": "."}
attributes_gff = {"ID": "CDS0", "Name": "CDS_0", "locus_tag": "AAA_00005"}
gene = Create_generator(gff_dict, attributes_gff, "gff")
checks = {"orphan": False, "int_anti": False}
output = mm.diff_strand_tss_gene(gene, tss, anti_ends, gene_ends,
checks, tss_entry)
self.assertEqual(output[0],
'utr_length=Primary_25,Antisense_NA;associated_gene=AAA_00001,AAA_00005;type=Primary,Antisense;Name=TSS_3+')
self.assertDictEqual(output[1], {
'Name': 'TSS_3+', 'utr_length': 'Primary_25,Antisense_NA',
'type': 'Primary,Antisense', 'associated_gene': 'AAA_00001,AAA_00005'})
def test_get_circrna(self):
circs = []
gffs = []
for index in range(0, 5):
circs.append(Create_generator(
self.example.circ_dict[index],
self.example.attributes_circ[index], "circ"))
for index in range(0, 3):
gffs.append(Create_generator(
self.example.gffs_dict[index],
self.example.attributes_gffs[index], "gff"))
out = StringIO()
out_best = StringIO()
args = self.mock_args.mock()
args.start_ratio = 0.3
args.end_ratio = 0.3
args.support = 5
nums = circ.get_circrna(circs, gffs, 50, out, out_best, args)
self.assertDictEqual(nums["support"], {
'aaa': {0: 2, 20: 1, 5: 2, 25: 1, 10: 2, 30: 1, 15: 1},
'all': {0: 3, 20: 1, 5: 3, 25: 1, 10: 2, 30: 1, 15: 1},
'bbb': {0: 1, 5: 1}})
self.assertDictEqual(nums["circular"], {'bbb': 1, 'aaa': 2, 'all': 3})
self.assertDictEqual(nums["conflict"], {'bbb': {0: 1, 5: 1},
'aaa': {},
'all': {0: 1, 5: 1}})
def test_detect_coverage(self):
tss = {
"seq_id": "aaa",
"source": "Refseq",
"feature": "TSS",
"start": 2,
"end": 2,
"phase": ".",
"strand": "+",
"score": "."
}
ref = {
"seq_id": "aaa",
"source": "Refseq",
"feature": "TSS",
"start": 3,
"end": 3,
"phase": ".",
"strand": "+",
"score": "."
}
attributes_tss = {"type": "Primary", "ID": "tss0", "Name": "TSS:2_+"}
attributes_ref = {"type": "Primary", "ID": "tss1", "Name": "TSS:3_+"}
tss_diff, ref_diff = co.detect_coverage(
self.example.wigs_f, Create_generator(tss, attributes_tss, "gff"),
Create_generator(ref, attributes_ref, "gff"))
self.assertEqual(tss_diff, 100)
self.assertEqual(ref_diff, 50)
def test_detect_conflict(self):
circ_dict = {
"seq_id": "aaa",
"source": "Refseq",
"feature": "circRNA",
"start": 100,
"end": 467,
"phase": ".",
"strand": "+",
"score": ".",
"support": 30,
"start_site": 30,
"end_site": 35,
"situation": "P",
"splice_type": "C"
}
attributes_circ = {"ID": "circrna0", "Name": "circRNA_0"}
circrna = Create_generator(circ_dict, attributes_circ, "circ")
gffs = [
Create_generator(self.example.cds_dict,
self.example.attributes_cds, "gff")
]
args = self.mock_args.mock()
args.start_ratio = 0.3
args.end_ratio = 0.3
args.support = 5
out = StringIO()
out_best = StringIO()
circ.detect_conflict(gffs, circrna, 0, out, out_best, args)
self.assertEqual(
out.getvalue(),
"circRNA_0 aaa + 100 467 AAA_00001 30 1.0 0.8571428571428571\n")
out.close()
class Example(object):
gff_dict = [
{"seq_id": "aaa", "source": "Refseq", "feature": "CDS", "start": 3,
"end": 30, "phase": ".", "strand": "+", "score": "."},
{"seq_id": "aaa", "source": "Refseq", "feature": "CDS", "start": 14,
"end": 35, "phase": ".", "strand": "-", "score": "."},
{"seq_id": "aaa", "source": "Refseq", "feature": "CDS", "start": 37,
"end": 55, "phase": ".", "strand": "-", "score": "."},
{"seq_id": "aaa", "source": "Refseq", "feature": "CDS", "start": 40,
"end": 66, "phase": ".", "strand": "+", "score": "."},
{"seq_id": "bbb", "source": "Refseq", "feature": "CDS", "start": 4,
"end": 25, "phase": ".", "strand": "-", "score": "."}]
attributes_gff = [
{"ID": "cds0", "Name": "CDS_0", "locus_tag": "AAA_00001"},
{"ID": "cds1", "Name": "CDS_1", "locus_tag": "AAA_00002",
"protein_id": "YP_500332.1"},
{"ID": "cds2", "Name": "CDS_2"},
{"ID": "cds3", "Name": "CDS_3", "locus_tag": "AAA_00003"},
{"ID": "cds4", "Name": "CDS_4", "locus_tag": "BBB_00001"}]
ta_dict = [{"seq_id": "aaa", "source": "Refseq",
"feature": "Transcript", "start": 1,
"end": 367, "phase": ".", "strand": "+", "score": "."},
{"seq_id": "aaa", "source": "Refseq",
"feature": "Transcript", "start": 230,
"end": 240, "phase": ".", "strand": "+", "score": "."},
{"seq_id": "bbb", "source": "Refseq",
"feature": "Transcript", "start": 430,
"end": 5167, "phase": ".", "strand": "-", "score": "."}]
attributes_tas = [
{"ID": "tran0", "Name": "Transcript_0", "locus_tag": "AAA_00001"},
{"ID": "tran1", "Name": "Transcript_1", "locus_tag": "AAA_00002"},
{"ID": "tran2", "Name": "Transcript_2", "locus_tag": "BBB_00001"}]
tss_dict = [{"seq_id": "aaa", "source": "Refseq",
"feature": "TSS", "start": 2,
"end": 2, "phase": ".", "strand": "+", "score": "."},
{"seq_id": "aaa", "source": "Refseq",
"feature": "TSS", "start": 230,
"end": 230, "phase": ".", "strand": "+", "score": "."},
{"seq_id": "bbb", "source": "Refseq",
"feature": "TSS", "start": 5166,
"end": 5166, "phase": ".", "strand": "-", "score": "."}]
attributes_tss = [{"ID": "tss0", "Name": "TSS_0", "type": "Primary",
"associated_gene": "AAA_00001"},
{"ID": "tss1", "Name": "TSS_1", "type": "Internal",
"associated_gene": "AAA_00002"},
{"ID": "tss2", "Name": "TSS_2", "type": "Orphan",
"associated_gene": "orphan"}]
gffs = []
tas = []
tsss = []
for index in range(0, 3):
gffs.append(Create_generator(gff_dict[index],
attributes_gff[index], "gff"))
tas.append(Create_generator(ta_dict[index],
attributes_tas[index], "gff"))
tsss.append(Create_generator(tss_dict[index],
attributes_tss[index], "gff"))
seq = {"aaa": "AAAATTATAGGCGTAGTAACCTCTTGATAGCGATGGATATAGACCCTTATAAGGCCTCTGATTAGAAAATAGGTAGGCCCCCGGGGGTGTGTAATAGATAGAT",
"bbb": "ATATGTACCCCGCGCCGTATAGCTATAAATTCGCTGCTTATTTTATA"}
class Example(object):
tar_dict = [{"seq_id": "aaa", "source": "Refseq",
"feature": "TSS", "start": 3,
"end": 3, "phase": ".", "strand": "+", "score": "."},
{"seq_id": "aaa", "source": "Refseq",
"feature": "TSS", "start": 24,
"end": 24, "phase": ".", "strand": "+", "score": "."},
{"seq_id": "aaa", "source": "Refseq",
"feature": "TSS", "start": 1243,
"end": 1243, "phase": ".", "strand": "+", "score": "."}]
attributes_tar = [{"coverage": "3", "ID": "tss1", "Name": "TSS:3_+"},
{"coverage": "340", "ID": "tss2", "Name": "TSS:24_+"},
{"coverage": "4440", "ID": "tss3", "Name": "TSS:1243_+"}]
ref_dict = [{"seq_id": "aaa", "source": "Refseq",
"feature": "TSS", "start": 3,
"end": 3, "phase": ".", "strand": "+", "score": "."},
{"seq_id": "aaa", "source": "Refseq",
"feature": "TSS", "start": 333,
"end": 333, "phase": ".", "strand": "+", "score": "."},
{"seq_id": "aaa", "source": "Refseq",
"feature": "TSS", "start": 1242,
"end": 1242, "phase": ".", "strand": "+", "score": "."}]
attributes_ref = [{"coverage": "3", "ID": "tss1", "Name": "TSS:3_+"},
{"coverage": "330", "ID": "tss2", "Name": "TSS:333_+"},
{"coverage": "1230", "ID": "tss3", "Name": "TSS:1242_+"}]
tars = []
refs = []
for index in range(0, 3):
tars.append(Create_generator(tar_dict[index],
attributes_tar[index], "gff"))
tars[-1].attributes["print"] = False
refs.append(Create_generator(ref_dict[index],
attributes_ref[index], "gff"))
refs[-1].attributes["print"] = False
class Example(object):
srnas = {"RNAplex": {"srna0": [{"target": "AAA_00001", "energy": -6.5, "rank": 1, "srna_pos": "2,10", "tar_pos": "10,15"},
{"target": "AAA_00002|dnaA", "energy": -3.5, "rank": 2, "srna_pos": "2,7", "tar_pos": "3,15"}],
"srna1": [{"target": "AAA_00003", "energy": -10.5, "rank": 1, "srna_pos": "2,10", "tar_pos": "10,15"}],
"srna2": [{"target": "AAA_00001", "energy": -23.5, "rank": 1, "srna_pos": "2,10", "tar_pos": "10,15"},
{"target": "AAA_00002|dnaA", "energy": -3.43, "rank": 3, "srna_pos": "2,10", "tar_pos": "10,15"},
{"target": "AAA_00003", "energy": -6.5, "rank": 2, "srna_pos": "2,10", "tar_pos": "10,15"}]},
"RNAup": {"srna0": [{"target": "AAA_00001", "energy": -6.5, "rank": 1, "srna_pos": "2,10", "tar_pos": "10,15"},
{"target": "AAA_00002|dnaA", "energy": -3.5, "rank": 2, "srna_pos": "2,10", "tar_pos": "10,15"}],
"srna1": [{"target": "AAA_00003", "energy": -10.5, "rank": 1, "srna_pos": "2,10", "tar_pos": "10,15"}],
"srna2": [{"target": "AAA_00001", "energy": -23.5, "rank": 1, "srna_pos": "2,10", "tar_pos": "10,15"}]}}
srna_dict = [{"start": 6, "end": 15, "phase": ".",
"strand": "+", "seq_id": "aaa", "score": ".",
"source": "Refseq", "feature": "sRNA"},
{"start": 1258, "end": 2234, "phase": ".",
"strand": "+", "seq_id": "aaa", "score": ".",
"source": "Refseq", "feature": "sRNA"},
{"start": 3544, "end": 6517, "phase": ".",
"strand": "-", "seq_id": "aaa", "score": ".",
"source": "Refseq", "feature": "sRNA"}]
attributes_srna = [{"ID": "srna0", "Name": "sRNA_0"},
{"ID": "srna1", "Name": "sRNA_1"},
{"ID": "srna2", "Name": "sRNA_2"}]
gff_dict = [{"start": 100, "end": 150, "phase": ".",
"strand": "+", "seq_id": "aaa", "score": ".",
"source": "Refseq", "feature": "CDS"},
{"start": 2348, "end": 2934, "phase": ".",
"strand": "+", "seq_id": "aaa", "score": ".",
"source": "Refseq", "feature": "CDS"},
{"start": 5544, "end": 5597, "phase": ".",
"strand": "-", "seq_id": "aaa", "score": ".",
"source": "Refseq", "feature": "CDS"}]
attributes_gff = [{"ID": "cds0", "Name": "CDS_0", "locus_tag": "AAA_00001"},
{"ID": "cds0", "Name": "CDS_1", "locus_tag": "AAA_00002"},
{"ID": "cds1", "Name": "CDS_2", "locus_tag": "AAA_00003"}]
srna_gffs = []
gffs = []
for index in range(0, 3):
srna_gffs.append(Create_generator(srna_dict[index], attributes_srna[index], "gff"))
gffs.append(Create_generator(gff_dict[index], attributes_gff[index], "gff"))
out_rna_txt = """>SAOUHSC_00001|dnaA
>srna1023
((((((&)))))) 571,576 : 20,25 (-5.30 = -7.89 + 0.18 + 2.41)"""
out_print = """sRNA strain sRNA_position sRNA_interacted_position_RNAplex sRNA_strand target target_position target_interacted_position_RNAplex target_strand energy_RNAplex rank_RNAplex
sRNA_1 aaa 1258-2234 1259-1267 + AAA_00003 5544-5597 5550-5545 - -10.5 1
sRNA_2 aaa 3544-6517 6508-6516 - AAA_00001 100-150 89-94 + -23.5 1
sRNA_2 aaa 3544-6517 6508-6516 - AAA_00003 5544-5597 5550-5545 - -6.5 2
sRNA_0 aaa 6-15 7-15 + AAA_00001 100-150 89-94 + -6.5 1
sRNA_0 aaa 6-15 7-12 + AAA_00002|dnaA 2348-2934 2330-2342 + -3.5 2
"""
rnaup = """>srna1023
>SAOUHSC_00001|dnaA
.(((((&))))). 571,576 : 20,25 (-4.87 = -8.00 + 0.31 + 2.81)
AACCUC&GGGGUU
>SAOUHSC_00002
(((..((((((((((((&)))))))))))).))) 14,30 : 11,26 (-5.91 = -13.15 + 4.20 + 3.05)
GAAGAUCCUAUUUUUAA&UUAAAAAUGGGGGUUC
"""
rnaplex = """>SAOUHSC_00001|dnaA
def read_file(self, gff_file, input_file, hypo):
self.circs = []
self.gffs = []
for index in range(0, 5):
self.circs.append(Create_generator(self.example.circ_dict[index],
self.example.attributes_circ[index], "circ"))
for index in range(0, 3):
self.gffs.append(Create_generator(self.example.gffs_dict[index],
self.example.attributes_gffs[index], "gff"))
return self.circs, self.gffs, 50
class Example(object):
seq_file = """>aaa
AGGATAGTCCGATACGTATACTGATAAAGACCGAAAATATTAGCGCGTAGC"""
gff_file = """aaa\tRefseq\tgene\t1\t12\t.\t+\t.\tID=gene_0;Name=GENE_0;locus_tag=AAA_00001
aaa\tRefseq\tCDS\t1\t12\t.\t+\t.\tID=cds_0;Name=CDS_0;locus_tag=AAA_00001;protein_id="YP.00001
aaa\tRefseq\tgene\t14\t34\t.\t-\t.\tID=gene_1;Name=gene_1;locus_tag=AAA_00002
aaa\tRefseq\tCDS\t14\t34\t.\t-\t.\tID=cds_1;Name=CDS_1;locus_tag=AAA_00002;protein_id="YP.00002"""
gene_dict = [{"seq_id": "aaa", "source": "Refseq", "feature": "gene", "start": 1,
"end": 10, "phase": ".", "strand": "+", "score": "."},
{"seq_id": "aaa", "source": "Refseq", "feature": "gene", "start": 12,
"end": 23, "phase": ".", "strand": "+", "score": "."},
{"seq_id": "aaa", "source": "Refseq", "feature": "gene", "start": 25,
"end": 30, "phase": ".", "strand": "-", "score": "."},
{"seq_id": "aaa", "source": "Refseq", "feature": "gene", "start": 33,
"end": 43, "phase": ".", "strand": "-", "score": "."}]
cdsf_dict = [{"seq_id": "aaa", "source": "Refseq", "feature": "CDS", "start": 1,
"end": 10, "phase": ".", "strand": "+", "score": "."},
{"seq_id": "aaa", "source": "Refseq", "feature": "rRNA", "start": 12,
"end": 23, "phase": ".", "strand": "+", "score": "."}]
cdsr_dict = [{"seq_id": "aaa", "source": "Refseq", "feature": "CDS", "start": 25,
"end": 30, "phase": ".", "strand": "+", "score": "."},
{"seq_id": "aaa", "source": "Refseq", "feature": "rRNA", "start": 33,
"end": 43, "phase": ".", "strand": "+", "score": "."}]
attributes_gene = [{"ID": "gene0", "Name": "danA", "locus_tag": "AAA_00001"},
{"ID": "gene1", "Name": "AAA_00002", "locus_tag": "AAA_00002"},
{"ID": "gene2", "Name": "AAA_00003", "locus_tag": "AAA_00003"},
{"ID": "gene3", "Name": "hrcA", "locus_tag": "AAA_00004"}]
attributes_cdsf = [{"ID": "cds0", "Name": "CDS_0", "locus_tag": "AAA_00001", "protein_id": "YP_000001", "Parent": "gene0"},
{"ID": "cds1", "Name": "CDS_1", "locus_tag": "AAA_00002"}]
attributes_cdsr = [{"ID": "cds2", "Name": "CDS_2", "locus_tag": "AAA_00003", "protein_id": "YP_000004", "Parent": "gene2"},
{"ID": "cds3", "Name": "CDS_3", "locus_tag": "AAA_00004"}]
fasta = "AGGATAGTCCGATACGTATACTGATAAAGACCGAAAATATTAGCGCGTAGC"
genes = []
cdss_f = []
cdss_r = []
for index in range(0, 2):
cdss_f.append(Create_generator(cdsf_dict[index], attributes_cdsf[index], "gff"))
cdss_r.append(Create_generator(cdsr_dict[index], attributes_cdsr[index], "gff"))
for index in range(0, 4):
genes.append(Create_generator(gene_dict[index], attributes_gene[index], "gff"))
cdsf_result = """>AAA_00001|danA
AGGATAGTCCGATACGTATACTGATAAAGACCGAAAATATTAGCGCGTAGC
>AAA_00002|CDS_1
AGGATAGTCCGATACGTATACTGATAAAGACCGAAAATATTAGCGCGTAGC"""
cdsr_result = """>AAA_00003
AGGATAGTCCGATACGTATACTGATAAAGACCGAAAATATTAGCGCGTAGC
>AAA_00004|CDS_3
AGGATAGTCCGATACGTATACTGATAAAGACCGAAAATATTAGCGCGTAGC"""
all_result = """>AAA_00001|CDS_0
def test_detect_overlap(self):
pre_dict = {
"seq_id": "aaa",
"source": "Refseq",
"feature": "sRNA",
"start": 3,
"end": 33,
"phase": ".",
"strand": "+",
"score": "."
}
attributes_pre = {"ID": "sRNA0", "Name": "srna_0", "sRNA_type": "5utr"}
tar1_dict = {
"seq_id": "aaa",
"source": "Refseq",
"feature": "sRNA",
"start": 3,
"end": 33,
"phase": ".",
"strand": "+",
"score": "."
}
attributes_tar1 = {
"ID": "sRNA0",
"Name": "srna_0",
"sRNA_type": "3utr"
}
tar2_dict = {
"seq_id": "aaa",
"source": "Refseq",
"feature": "sRNA",
"start": 53,
"end": 233,
"phase": ".",
"strand": "+",
"score": "."
}
attributes_tar2 = {
"ID": "sRNA0",
"Name": "srna_0",
"sRNA_type": "5utr"
}
pre = Create_generator(pre_dict, attributes_pre, "gff")
tar1 = Create_generator(tar1_dict, attributes_tar1, "gff")
tar2 = Create_generator(tar2_dict, attributes_tar2, "gff")
overlap = False
overlap = ms.detect_overlap(tar1, pre, "UTR", overlap)
self.assertTrue(overlap)
overlap = False
overlap = ms.detect_overlap(tar2, pre, "UTR", overlap)
self.assertFalse(overlap)
def test_get_feature(self):
attributes_cds = {"ID": "cds0", "Name": "CDS_0", "locus_tag": "AAA_00001",
"protein_id": "YP_918384.3"}
attributes = circ.get_feature(Create_generator(self.example.cds_dict,
attributes_cds, "gff"))
self.assertEqual(attributes, "AAA_00001")
attributes_cds = {"ID": "cds0", "Name": "CDS_0", "protein_id": "YP_918384.3"}
attributes = circ.get_feature(Create_generator(self.example.cds_dict,
attributes_cds, "gff"))
self.assertEqual(attributes, "YP_918384.3")
attributes_cds = {"ID": "cds0", "Name": "CDS_0"}
attributes = circ.get_feature(Create_generator(self.example.cds_dict,
attributes_cds, "gff"))
self.assertEqual(attributes, "cds0:122-267_f")
def test_gen_batch(self):
gs.import_wig = Mock_func().mock_import_wig
out = StringIO()
lib_t = "wig1 wig2"
lib_n = "wig3 wig4"
lib_f = "wig5"
gff_dict = {
"seq_id": "aaa",
"source": "Refseq",
"feature": "CDS",
"start": 3,
"end": 6,
"phase": ".",
"strand": "+",
"score": "."
}
attributes_gff = {
"ID": "CDS0",
"Name": "CDS_0",
"locus_tag": "AAA_00001"
}
gff = Create_generator(gff_dict, attributes_gff, "gff")
seq = {"aaa": "ATATGGCCGACGAGTTCGACGATACAACCCGTGGGG"}
gs.gen_batch(lib_t, lib_n, lib_f, "+", [gff], out, seq)
self.assertEqual(out.getvalue(), self.example.out_print_wig)
def test_set_cutoff(self):
detects = {}
detects["express"] = 100
gff_dict = {
"seq_id": "aaa",
"source": "Refseq",
"feature": "CDS",
"start": 3,
"end": 102,
"phase": ".",
"strand": "+",
"score": "."
}
attributes_gff = {
"ID": "CDS0",
"Name": "CDS_0",
"locus_tag": "AAA_00001"
}
gff = Create_generator(gff_dict, attributes_gff, "gff")
diff, cutoff_percent = gea.set_cutoff("tex", "all", "all", detects,
gff)
self.assertEqual(diff, 100)
self.assertEqual(cutoff_percent, 0)
diff, cutoff_percent = gea.set_cutoff("frag", "all", "n_50", detects,
gff)
self.assertEqual(diff, 100)
self.assertEqual(cutoff_percent, 50)
diff, cutoff_percent = gea.set_cutoff("tex", "p_0.5", "n_50", detects,
gff)
self.assertEqual(diff, 1.0)
self.assertEqual(cutoff_percent, 0.5)
def test_detect_inter_type(self):
inter_dict = [{
"seq_id": "aaa",
"source": "UTR_derived",
"feature": "Transcript",
"start": 1,
"end": 23,
"phase": ".",
"strand": "+",
"score": "."
}]
attributes_inter = [{
"ID": "tran0",
"Name": "Transcript_0",
"UTR_type": "3utr"
}]
inters = []
inters.append(
Create_generator(inter_dict[0], attributes_inter[0], "gff"))
sd.get_coverage = self.mock.mock_get_coverage
wigs = {"forward": "wigs_f", "reverse": "wigs_r"}
data = sd.detect_inter_type(inters, wigs, "test")
self.assertDictEqual(
data, {'aaa': {
'interCDS': [],
'5utr': [],
'3utr': ['2']
}})
sd.get_coverage = copy.deepcopy(get_coverage)
def test_detect_express(self):
gff_dict = {
"seq_id": "aaa",
"source": "Refseq",
"feature": "CDS",
"start": 3,
"end": 5,
"phase": ".",
"strand": "+",
"score": "."
}
attributes_gff = {
"ID": "CDS0",
"Name": "CDS_0",
"locus_tag": "AAA_00001"
}
gff = Create_generator(gff_dict, attributes_gff, "gff")
texs = {"tex1_tex2": 0}
plots = {"frag": {}}
detects = {"cond": 0, "track": 0, "import": False, "express": 0}
gea.detect_express(self.example.wig_frags["aaa"]["frag"]["track_1"],
gff, 5, detects, "all", "all", texs, "frag", 2,
"track_1", plots, "high", "frag")
self.assertDictEqual(
{
'track': 1,
'import': False,
'cond': 0,
'express': 2
}, detects)
def test_fix_primary_type(self):
tss_dict = [{
"seq_id": "aaa",
"source": "Refseq",
"feature": "TSS",
"start": 2,
"end": 2,
"phase": ".",
"strand": "+",
"score": "."
}, {
"seq_id": "aaa",
"source": "Refseq",
"feature": "TSS",
"start": 3,
"end": 3,
"phase": ".",
"strand": "+",
"score": "."
}, {
"seq_id": "aaa",
"source": "Refseq",
"feature": "TSS",
"start": 4,
"end": 4,
"phase": ".",
"strand": "+",
"score": "."
}]
attributes = [{
"type": "Primary",
"ID": "tss0",
"Name": "TSS:2_+",
"UTR_length": "Primary_10",
"associated_gene": "AAA_00001"
}, {
"type": "Primary&Internal",
"ID": "tss1",
"Name": "TSS:3_+",
"UTR_length": "Primary_20&Internal_NA",
"associated_gene": "AAA_00001&AAA_00005"
}, {
"type": "Primary&Primary",
"ID": "tss2",
"Name": "TSS:4_+",
"UTR_length": "Primary_40&Primary_60",
"associated_gene": "AAA_00001&AAA_00004"
}]
tsss = []
for index in range(0, 3):
tsss.append(
Create_generator(tss_dict[index], attributes[index], "gff"))
new_tsss = co.fix_primary_type(tsss, self.example.wigs_f,
self.example.wigs_r)
utrs = []
for tss in new_tsss:
utrs.append(tss.attributes["UTR_length"])
self.assertEqual(
set(utrs),
set(["Internal_NA&Secondary_20", "Primary_60", "Primary_10"]))
def mock_read_gff(self, srna_file, data_type):
srnas = []
for index in range(0, 2):
srnas.append(
Create_generator(self.example.srna_dict[index],
self.example.attributes_srna[index], "gff"))
return srnas
class Example(object):
wigs = {
"aaa": {
"frag_1": {
"track_1|+|frag": [
100, 30, 23, 21, 21, 2, 100, 30, 23, 21, 21, 2, 100, 30,
23, 21, 21, 2, 100, 30, 23, 21, 21, 2
]
}
}
}
ta_dict = [{
"seq_id": "aaa",
"source": "ANNOgesic",
"feature": "Transcript",
"start": 4,
"end": 20,
"phase": ".",
"strand": "+",
"score": "."
}]
attributes_tas = [{
"ID": "tran0",
"Name": "Transcript_0",
"detect_lib": "fragmented&tex_notex"
}]
tas = []
for index in range(0, 1):
tas.append(
Create_generator(ta_dict[index], attributes_tas[index], "gff"))
def test_compare_tran(self):
tran_dict = {
"seq_id": "aaa",
"source": "Refseq",
"feature": "Transcript",
"start": 100,
"end": 500,
"phase": ".",
"strand": "+",
"score": "."
}
attributes_tran = {"ID": "tran0", "Name": "Tran_0"}
out = StringIO()
gffs = read_dict(3, self.example.gff_dict, self.example.attributes_gff)
tran = Create_generator(tran_dict, attributes_tran, "gff")
c_gff.compare_tran(gffs, tran, out)
datas, attributes = extract_info(out.getvalue(), "string")
parents = []
for attribute in attributes:
for element in attribute:
if "Parent" in element:
parents.append(element)
self.assertEqual(set(datas),
set(["aaa\tRefseq\tCDS\t160\t300\t.\t+\t."]))
self.assertEqual(set(parents), set(["Parent=tran0"]))
out.close()
def test_fix_primary_type(self):
wigs = {"aaa": {"track_1": [{"pos": 1, "coverage": 200},
{"pos": 2, "coverage": 300},
{"pos": 3, "coverage": 400},
{"pos": 4, "coverage": 600},
{"pos": 5, "coverage": 650},
{"pos": 6, "coverage": 655}]}}
tss_dict = [{"seq_id": "aaa", "source": "Refseq",
"feature": "TSS", "start": 3,
"end": 3, "phase": ".", "strand": "+", "score": "."},
{"seq_id": "aaa", "source": "Refseq",
"feature": "TSS", "start": 5,
"end": 5, "phase": ".", "strand": "+", "score": "."}]
attributes_tss = [{"ID": "CDS0", "Name": "CDS_0",
"type": "Primary,Primary",
"associated_gene": "AAA_00001,AAA_00002",
"utr_length": "Primary_25,Primary_200"},
{"ID": "CDS1", "Name": "CDS_1",
"type": "Primary,Antisense",
"associated_gene": "AAA_00001,AAA_00004",
"utr_length": "Primary_27,Antisense_NA"}]
tsss = []
for index in range(0, 2):
tsss.append(Create_generator(
tss_dict[index], attributes_tss[index], "gff"))
mm.fix_primary_type(tsss, wigs, "test")
self.assertEqual(tsss[0].attributes["type"], "Primary")
self.assertEqual(tsss[1].attributes["type"], "Antisense,Secondary")
def entries(self, fh):
for line in fh:
if "gff" in line:
lists = self.example.gff_dict
attributes = self.example.attributes_gff
num = 3
elif "tran" in line:
lists = self.example.tran_dict
attributes = self.example.attributes_tran
num = 3
elif "term" in line:
lists = self.example.term_dict
attributes = self.example.attributes_term
num = 3
elif "tss" in line:
lists = self.example.tss_dict
attributes = self.example.attributes_tss
num = 3
elif "utr5" in line:
lists = self.example.utr5_dict
attributes = self.example.attributes_utr5
num = 2
elif "utr3" in line:
lists = self.example.utr3_dict
attributes = self.example.attributes_utr3
num = 2
for index in range(0, num):
yield Create_generator(lists[index], attributes[index], "gff")
def test_compare_term(self):
ta_dict = {"seq_id": "aaa", "source": "Refseq", "feature": "TSS", "start": 138,
"end": 540, "phase": ".", "strand": "+", "score": "."}
attributes_ta = {"ID": "tran0", "Name": "Transcript_0"}
ta = Create_generator(ta_dict, attributes_ta, "gff")
term = du.compare_term(ta, self.example.terms, 5)
self.assertEqual(term.start, 530)
def test_compare_wigs(self):
gff_dict = {
"seq_id": "aaa",
"source": "Refseq",
"feature": "CDS",
"start": 3,
"end": 5,
"phase": ".",
"strand": "+",
"score": "."
}
attributes_gff = {
"ID": "CDS0",
"Name": "CDS_0",
"locus_tag": "AAA_00001"
}
gff = Create_generator(gff_dict, attributes_gff, "gff")
texs = {"tex1_tex2": 0}
replicates = {"tex": 1, "frag": 1}
stats = {
"CDS": {
"total": {
"total": 0,
"least_one": 0,
"all": 0,
"none": 0
},
"aaa": {
"total": 0,
"least_one": 0,
"all": 0,
"none": 0
}
}
}
outs = {"CDS": {"least_one": [], "all": [], "none": []}}
plots = {}
gea.compare_wigs(self.example.wig_texs, gff, 2, texs, replicates,
stats["CDS"], outs["CDS"], plots, "high", 5, "all",
"all")
self.assertDictEqual(
stats, {
'CDS': {
'total': {
'tex': 1,
'none': 0,
'total': 0,
'all': 1,
'least_one': 1
},
'aaa': {
'tex': 1,
'none': 0,
'total': 0,
'all': 1,
'least_one': 1
}
}
})
def test_del_repeat(self):
tss_dict = [{
"seq_id": "aaa",
"source": "Refseq",
"feature": "TSS",
"start": 2,
"end": 2,
"phase": ".",
"strand": "+",
"score": "."
}, {
"seq_id": "aaa",
"source": "Refseq",
"feature": "TSS",
"start": 22,
"end": 22,
"phase": ".",
"strand": "+",
"score": "."
}, {
"seq_id": "aaa",
"source": "Refseq",
"feature": "TSS",
"start": 122,
"end": 122,
"phase": ".",
"strand": "-",
"score": "."
}]
attributes = [{
"type": "Primary",
"ID": "tss0",
"Name": "TSS:2_+",
"UTR_length": "Primary_100",
"associated_gene": "AAA_00001"
}, {
"type": "Primary&Primary",
"ID": "tss1",
"Name": "TSS:22_+",
"UTR_length": "Primary_20&Primary_50",
"associated_gene": "AAA_00004&AAA_00005"
}, {
"type": "Secondary&Internal",
"ID": "tss2",
"Name": "TSS:122_-",
"UTR_length": "Secondary_220&Internal_NA",
"associated_gene": "AAA_00008&AAA_00009"
}]
tsss = []
for index in range(0, 3):
tsss.append(
Create_generator(tss_dict[index], attributes[index], "gff"))
co.del_repeat(tsss)
utrs = []
for tss in tsss:
utrs.append(tss.attributes["UTR_length"])
self.assertEqual(
set(utrs),
set(["Primary_100", "Primary_20", "Internal_NA&Secondary_220"]))
