def test_cpm():
dge_list = DGEList(filename=str(get_dataset_path(TEST_DATASET_NPZ)))
first_pos = dge_list.counts[0][0]
col_sum = np.sum(dge_list.counts, axis=0)
assert isinstance(first_pos, np.integer)
new_dge_list = dge_list.cpm()
assert new_dge_list.counts[0][0] == first_pos * 1e6 / col_sum[0]
def test_tpm():
# example hand calculated as in https://www.youtube.com/watch?time_continue=611&v=TTUrtCY2k-w
counts = np.array([[10, 12, 30], [20, 25, 60], [5, 8, 15], [0, 0, 1]])
gene_lengths = np.array([2000, 4000, 1000, 10000])
expected = np.array(
[
[333_333.333_333_33, 296_296.296_296_3, 332_594.235_033_26],
[333_333.333_333_33, 308_641.975_308_64, 332_594.235_033_26],
[333_333.333_333_33, 395_061.728_395_06, 332_594.235_033_26],
[0.0, 0.0, 2217.294_900_22],
]
)
dge_list = DGEList(
counts=counts,
samples=np.array(['a', 'b', 'c']),
genes=np.array(['a', 'b', 'c', 'd']),
groups_in_dict={'group1': ['a', 'c'], 'group2': ['b', 'd']},
)
assert isinstance(dge_list.counts[0][0], np.integer)
new_dge_list = dge_list.tpm(gene_lengths)
assert np.allclose(new_dge_list.counts, expected, atol=1e-1)
# make sure that the sums of all genes across are the same the each sample (an important property of TPM)
gene_sums = new_dge_list.counts.sum(axis=0)
assert np.allclose(gene_sums, [gene_sums[0]] * len(gene_sums))
def test_minimal_init():
dge_list = DGEList(
to_remove_zeroes=False,
counts=np.ones(shape=(5, 5)),
samples=["A", "B", "C", "D", "E"],
genes=["ENSG001", "ENSG002", "ENSG003", "ENSG004", "ENSG005"],
groups_in_dict={'group1': ["A", "B"], 'group2': ["C", "D", "E"]},
)
assert dge_list.__repr__() == "DGEList(num_samples=5, num_genes=5)"
def test_init():
dge_list = DGEList.create_DGEList_data_file(
data_file=get_dataset_path(TEST_DATASET), group_file=get_dataset_path(TEST_GROUPS)
)
assert dge_list.__repr__() == "DGEList(num_samples=10, num_genes=21,711)"
dge_list = DGEList.create_DGEList_handle(
data_handle=smart_open(get_dataset_path(TEST_DATASET)),
group_handle=smart_open(get_dataset_path(TEST_GROUPS)),
)
assert dge_list.__repr__() == "DGEList(num_samples=10, num_genes=21,711)"
def test_rpkm():
dge_list = DGEList(filename=str(get_dataset_path(TEST_DATASET_NPZ)))
icd = CanonicalDataStore(
get_dataset_path(TEST_GENE_SET_DATA), get_dataset_path(TEST_GENE_SYMBOLS)
)
first_pos = dge_list.counts[0][0]
first_gene = dge_list.genes[0]
col_sum = np.sum(dge_list.counts, axis=0)
assert isinstance(first_pos, np.integer)
rpm_dge = dge_list.rpkm(icd)
ensg_gene = icd.pick_gene_id(icd.get_genes_from_symbol(first_gene))
gene_len = icd.get_length_of_canonical_transcript(ensg_gene)
# RPKM=numReads / (geneLength / 1000 * totalNumReads / 1, 000, 000)
assert rpm_dge.counts[0][0] == (first_pos / ((gene_len / 1e3) * (col_sum[0] / 1e6)))
def test_create_DGEList_handle_init():
dge_list = DGEList.create_DGEList_handle(
data_handle=smart_open(get_dataset_path(TEST_DATASET)),
group_handle=smart_open(get_dataset_path(TEST_GROUPS)),
)
assert 2 == len(dge_list.groups_dict)
assert 5 == len(dge_list.groups_dict["Group 1"])
assert 5 == len(dge_list.groups_dict["Group 2"])
assert dge_list.samples.shape == dge_list.groups_list.shape
def testing_setting_samples_and_counts():
# Empty list should fail
with pytest.raises(Exception):
DGEList(
to_remove_zeroes=False,
groups_in_list=['A', 'A', 'A', 'A', 'A', 'B', 'B', 'B', 'B', 'B'],
)
# Lists with just counts should fail
with pytest.raises(ValueError):
DGEList(counts=np.array([[2, 2, 2], [2, 2, 2], [2, 2, 2]]), groups_in_list=['A', 'A', 'B'])
# lists sith samples and counts and groups should pass:
DGEList(
counts=np.array([[2, 2, 2], [2, 2, 2], [2, 2, 2]]),
groups_in_list=['A', 'A', 'B'],
samples=["S1", 'S2', 'S3'],
)
# Lists with just samples should fail
with pytest.raises(Exception):
DGEList(
samples=np.array(["1", "2", "3"]),
to_remove_zeroes=False,
groups_in_list=['A', 'A', 'B'],
)
# Properly formed samples and counts should pass
DGEList(
samples=np.array(["1", "2", "3"]),
counts=np.array([[2, 2, 2], [2, 2, 2], [2, 2, 2]]),
groups_in_list=['A', 'A', 'B'],
)
# Lists with ill-matched samples and counts should fail
pytest.raises(
ValueError,
"DGEList(samples = np.array(['2', '3']),"
" counts = np.array([[2, 2, 2], [2, 2, 2], [2, 2, 2]]))",
)
def test_cycle_dge_npz():
import tempfile
import os
tempdir = tempfile.mkdtemp(prefix="edgePy_tmp")
file_name = tempdir + os.sep + next(tempfile._get_candidate_names())
dge_list_first = dge_list()
dge_list_first.write_npz_file(filename=file_name)
dge_list_second = DGEList(filename=file_name + ".npz")
assert np.array_equal(dge_list_first.counts, dge_list_second.counts)
assert np.array_equal(dge_list_first.genes, dge_list_second.genes)
assert np.array_equal(dge_list_first.samples, dge_list_second.samples)
assert np.array_equal(dge_list_first.norm_factors, dge_list_second.norm_factors)
assert np.array_equal(dge_list_first.groups_list, dge_list_second.groups_list)
os.remove(file_name + ".npz")
os.rmdir(tempdir)
def test_library_size():
dge_list = DGEList(filename=str(get_dataset_path(TEST_DATASET_NPZ)))
assert np.array_equal(
dge_list.library_size,
np.array(
[
63_579_607,
58_531_933,
39_138_521,
78_565_885,
48_667_119,
62_799_917,
66_032_107,
66_194_776,
55_085_875,
37_760_315,
]
),
)
def test_create_DGEList():
"""Tests the function that converts data into a DGE_List object"""
samples = ["AAA", "BBB", "CCC"]
genes = ["ENSG001", "ENSG002"]
data_set = {
"AAA": {"ENSG001": 10, "ENSG002": 20},
"BBB": {"ENSG001": 15, "ENSG002": 40},
"CCC": {"ENSG001": 20, "ENSG002": 80},
}
categories = {"One": ["AAA", "BBB"], "Two": ["CCC"]}
dge_list = DGEList.create_DGEList(
sample_list=samples, data_set=data_set, gene_list=genes, category_to_samples=categories
)
assert np.array_equal(dge_list.samples, np.array(samples))
# 2 rows (genes), 3 columns(samples)
assert np.array_equal(dge_list.counts, np.array([[10, 15, 20], [20, 40, 80]]))
assert np.array_equal(dge_list.groups_list, np.array(["One", "One", "Two"]))
assert dge_list.groups_dict, {"One:"}
assert np.array_equal(dge_list.genes, np.array(genes))
def test_setting_DGElist_counts():
dge_list = DGEList(
counts=np.zeros(shape=(5, 10)),
groups_in_list=['A', 'A', 'B', 'B', 'B'],
samples=['S0', 'S1', 'S2', 'S3', 'S4', 'S5', 'S6', 'S7', 'S8', 'S9'],
)
assert 5 == dge_list.counts.shape[0]
assert 10 == dge_list.counts.shape[1]
with pytest.raises(ValueError):
c = np.array([[1, 1, 1], [-1, 1, 1]])
DGEList(counts=c, groups_in_list=["a", "b"])
with pytest.raises(ValueError):
c = np.array([[1, 1, 1], [np.nan, 1, 1]])
DGEList(counts=c, groups_in_list=["a", "b"])
with pytest.raises(ValueError):
c = np.array([1, 1, 1])
DGEList(counts=c, groups_in_list=["a", "b"])
with pytest.raises(TypeError):
c = [1, 1, 1]
dge_list.counts = c
def test_too_many_options2():
with pytest.raises(Exception):
DGEList(counts=np.ones(shape=(5, 10)), filename=str(get_dataset_path(TEST_DATASET_NPZ)))
def test_sample_group_list():
samples = ["A", "B", "C", "D", "E"]
sample_by_group = {'group1': ["A", "B"], 'group2': ["C", "D", "E"]}
expected_output = np.array(['group1', 'group1', 'group2', 'group2', 'group2'])
output = DGEList._sample_group_list(sample_by_group, samples)
assert np.array_equal(output, expected_output)
def test_broken_dge_caGENE_SYMBOL_SQLll():
with pytest.raises(Exception):
DGEList(filename="fake_filename", counts=np.array([[1, 1, 1], [1, 1, 1]]))
with pytest.raises(Exception):
DGEList(counts=None)
def dge_list():
with smart_open(get_dataset_path(TEST_DATASET), 'r') as data_handle, smart_open(
get_dataset_path(TEST_GROUPS), 'r'
) as group_handle:
return DGEList.create_DGEList_handle(data_handle, group_handle)
def __init__(self, args):
self.dge_list = None
if args.dge_file:
self.dge_list = DGEList(filename=args.dge_file)
log.info(f"The DGE list is {self.dge_list}")
elif args.mongo_config:
# This section is only useful for MongoDB based analyses. Talk to @apfejes about this section if you have
# any questions.
config = configparser.ConfigParser()
config.read(args.mongo_config)
if args.group1_sample_names and args.group2_sample_names:
key = 'sample_name'
value = args.group1_sample_names + args.group2_sample_names
elif args.key_name and args.mongo_key_value:
key = args.mongo_key_name
value = args.mongo_key_value
else:
raise ValueError("Insufficient parameters for use of Mongodb")
mongo_importer = ImportFromMongodb(
host=config.get("Mongo", "host"),
port=config.get("Mongo", "port"),
mongo_key=key,
mongo_value=value,
gene_list_file=args.gene_list,
)
sample_list, data_set, gene_list, sample_category = mongo_importer.get_data_from_mongo(
database=args.database_name
)
if key == 'sample_name':
# Override sample categories if sample name is the source of the categories.
sample_category_list = [
"group1" if sample_name in args.group1_sample_names else "group2"
for sample_name in sample_list
]
sample_category_dict = None
else:
# TODO: read from file
sample_category_dict = args.groups_json
sample_category_list = None
self.dge_list = DGEList.create_DGEList(
sample_list,
data_set,
gene_list,
sample_to_category=sample_category_list,
category_to_samples=sample_category_dict,
)
self.ensg_to_symbol = mongo_importer.mongo_reader.find_as_dict(
'ensembl_90_37', "symbol_by_ensg", query={}
)
else:
self.dge_list = DGEList.create_DGEList_data_file(
data_file=args.counts_file, group_file=args.groups_file
)
self.output = args.output if args.output else None
self.p_value_cutoff = args.cutoff
self.minimum_cpm = args.minimum_cpm
def test_sample_by_group():
samples = ["A", "B", "C", "D", "E"]
expected_output = {'group1': ["A", "B"], 'group2': ["C", "D", "E"]}
group_by_sample = ['group1', 'group1', 'group2', 'group2', 'group2']
output = DGEList._sample_group_dict(group_by_sample, samples)
assert output == expected_output