def test_read_10x():
anndata = read_10x_vdj("tests/data/10x/all_contig_annotations.json")
obs = anndata.obs
# this has `is_cell=false` and should be filtered out
assert "AAACCTGAGACCTTTG-1" not in anndata.obs_names
assert obs.shape[0] == 2
cell1 = obs.iloc[0, :]
cell2 = obs.iloc[1, :]
assert cell1.name == "AAACCTGAGACCTTTG-2"
assert cell1["TRB_1_cdr3"] == "CASSPPSQGLSTGELFF"
assert (
cell1["TRB_1_cdr3_nt"] == "TGTGCCAGCTCACCACCGAGCCAGGGCCTTTCTACCGGGGAGCTGTTTTTT"
)
assert cell1["TRB_1_junction_ins"] == 4 + 7
assert cell1["TRB_1_expr"] == 1
assert cell1["TRB_1_v_gene"] == "TRBV18"
assert cell1["TRB_1_d_gene"] == "TRBD1"
assert cell1["TRB_1_j_gene"] == "TRBJ2-2"
assert cell1["TRB_1_c_gene"] == "TRBC2"
assert _is_false(cell1["multi_chain"])
assert np.all(_is_na(cell1[["TRA_1_cdr3", "TRB_2_cdr3", "TRA_1_junction_ins"]]))
assert cell2.name == "AAACCTGAGTACGCCC-1"
assert cell2["TRA_1_cdr3"] == "CAMRVGGSQGNLIF"
assert cell2["TRA_2_cdr3"] == "CATDAKDSNYQLIW"
assert cell2["TRA_1_expr"] == 9
assert cell2["TRA_2_expr"] == 4
assert np.all(_is_na(cell2[["TRB_1_cdr3", "TRB_2_cdr3"]]))
assert cell2["TRA_1_junction_ins"] == 4
assert cell2["TRA_2_junction_ins"] == 4
def test_read_10x_csv():
anndata = read_10x_vdj(TESTDATA / "10x/filtered_contig_annotations.csv")
obs = anndata.obs
assert obs.shape[0] == 5
cell1 = obs.iloc[1, :]
cell2 = obs.iloc[3, :]
cell3 = obs.iloc[4, :]
assert cell1.name == "AAACCTGAGTACGCCC-1"
assert cell1["IR_VDJ_1_junction_aa"] == "CASSLGPSTDTQYF"
assert cell1[
"IR_VDJ_1_junction"] == "TGTGCCAGCAGCTTGGGACCTAGCACAGATACGCAGTATTTT"
assert cell1["IR_VDJ_1_duplicate_count"] == 55
assert cell1["IR_VDJ_1_consensus_count"] == 18021
assert cell1["IR_VDJ_1_v_call"] == "TRBV7-2"
assert cell1["IR_VDJ_1_d_call"] == "TRBD2"
assert cell1["IR_VDJ_1_j_call"] == "TRBJ2-3"
assert cell1["IR_VDJ_1_c_call"] == "TRBC2"
assert _is_false(cell1["multi_chain"])
assert cell1["IR_VJ_1_locus"] == "TRA"
assert cell1["IR_VDJ_1_locus"] == "TRB"
assert cell2.name == "AAACCTGGTCCGTTAA-1"
assert cell2["IR_VJ_1_junction_aa"] == "CALNTGGFKTIF"
assert cell2["IR_VJ_2_junction_aa"] == "CAVILDARLMF"
assert cell2["IR_VJ_1_duplicate_count"] == 5
assert cell2["IR_VJ_2_duplicate_count"] == 5
assert cell2["IR_VJ_1_locus"] == "TRA"
assert cell2["IR_VDJ_1_locus"] == "TRB"
assert cell2["IR_VJ_2_locus"] == "TRA"
assert _is_na(cell2["IR_VDJ_2_junction_aa"])
assert cell3.name == "AAACTTGGTCCGTTAA-1"
assert cell3["IR_VJ_1_locus"] == "IGK"
assert cell3["IR_VDJ_1_locus"] == "IGH"
def test_read_10x():
anndata = read_10x_vdj(TESTDATA / "10x/all_contig_annotations.json",
include_fields=None)
obs = anndata.obs
# this has `is_cell=false` and should be filtered out
assert "AAACCTGAGACCTTTG-1" not in anndata.obs_names
assert obs.shape[0] == 3
cell1 = obs.iloc[0, :]
cell2 = obs.iloc[1, :]
cell3 = obs.iloc[2, :]
assert cell1.name == "AAACCTGAGACCTTTG-2"
assert cell1["IR_VDJ_1_junction_aa"] == "CASSPPSQGLSTGELFF"
assert (cell1["IR_VDJ_1_junction"] ==
"TGTGCCAGCTCACCACCGAGCCAGGGCCTTTCTACCGGGGAGCTGTTTTTT")
assert cell1["IR_VDJ_1_np1_length"] == 4
assert cell1["IR_VDJ_1_np2_length"] == 7
assert cell1["IR_VDJ_1_duplicate_count"] == 1
assert cell1["IR_VDJ_1_consensus_count"] == 494
assert cell1["IR_VDJ_1_v_call"] == "TRBV18"
assert cell1["IR_VDJ_1_d_call"] == "TRBD1"
assert cell1["IR_VDJ_1_j_call"] == "TRBJ2-2"
assert cell1["IR_VDJ_1_c_call"] == "TRBC2"
assert _is_false(cell1["multi_chain"])
assert np.all(
_is_na(cell1[[
"IR_VJ_1_junction_aa", "IR_VDJ_2_junction_aa", "IR_VJ_1_np1_length"
]]))
assert cell2.name == "AAACCTGAGTACGCCC-1"
assert cell2["IR_VJ_1_junction_aa"] == "CAMRVGGSQGNLIF"
assert cell2["IR_VJ_2_junction_aa"] == "CATDAKDSNYQLIW"
assert cell2["IR_VJ_1_duplicate_count"] == 9
assert cell2["IR_VJ_2_duplicate_count"] == 4
assert np.all(
_is_na(cell2[["IR_VDJ_1_junction_aa", "IR_VDJ_2_junction_aa"]]))
assert cell2["IR_VJ_1_np1_length"] == 4
assert _is_na(cell2["IR_VJ_1_np2_length"])
assert cell2["IR_VJ_2_np1_length"] == 4
assert _is_na(cell2["IR_VJ_2_np2_length"])
assert cell3.name == "CAGGTGCTCGTGGTCG-1"
assert cell3["IR_VJ_1_locus"] == "IGK"
assert _is_na(cell3["IR_VJ_2_locus"]) # non-productive
assert cell3["IR_VDJ_1_locus"] == "IGH"
assert _is_na(cell3["IR_VDJ_2_locus"]) # non-productive
def test_read_10x_csv():
anndata = read_10x_vdj("tests/data/10x/filtered_contig_annotations.csv")
obs = anndata.obs
assert obs.shape[0] == 4
cell1 = obs.iloc[1, :]
cell2 = obs.iloc[3, :]
assert cell1.name == "AAACCTGAGTACGCCC-1"
assert cell1["TRB_1_cdr3"] == "CASSLGPSTDTQYF"
assert cell1["TRB_1_cdr3_nt"] == "TGTGCCAGCAGCTTGGGACCTAGCACAGATACGCAGTATTTT"
assert _is_na(cell1["TRB_1_junction_ins"])
assert cell1["TRB_1_expr"] == 55
assert cell1["TRB_1_v_gene"] == "TRBV7-2"
assert cell1["TRB_1_d_gene"] == "TRBD2"
assert cell1["TRB_1_j_gene"] == "TRBJ2-3"
assert cell1["TRB_1_c_gene"] == "TRBC2"
assert _is_false(cell1["multi_chain"])
assert cell2.name == "AAACCTGGTCCGTTAA-1"
assert cell2["TRA_1_cdr3"] == "CALNTGGFKTIF"
assert cell2["TRA_2_cdr3"] == "CAVILDARLMF"
assert cell2["TRA_1_expr"] == 5
assert cell2["TRA_2_expr"] == 5
assert _is_na(cell2["TRB_2_cdr3"])
def test_is_false():
warnings.filterwarnings("error")
assert _is_false(False)
assert _is_false(0)
assert _is_false("")
assert _is_false("False")
assert _is_false("false")
assert not _is_false(42)
assert not _is_false(True)
assert not _is_false("true")
assert not _is_false("foobar")
assert not _is_false(np.nan)
assert not _is_false(None)
assert not _is_false("nan")
assert not _is_false("None")
array_test = np.array(
["False", "false", 0, 1, True, False, "true", "Foobar", np.nan, "nan"],
dtype=object,
)
array_test_str = array_test.astype("str")
array_expect = np.array(
[True, True, True, False, False, True, False, False, False, False]
)
array_test_bool = np.array([True, False, True])
array_expect_bool = np.array([False, True, False])
npt.assert_equal(_is_false(array_test), array_expect)
npt.assert_equal(_is_false(array_test_str), array_expect)
npt.assert_equal(_is_false(pd.Series(array_test)), array_expect)
npt.assert_equal(_is_false(pd.Series(array_test_str)), array_expect)
npt.assert_equal(_is_false(array_test_bool), array_expect_bool)
npt.assert_equal(_is_false(pd.Series(array_test_bool)), array_expect_bool)
def test_is_false():
warnings.filterwarnings("error")
assert _is_false(False)
assert _is_false(0)
# assert _is_false("") -> I redelacred this as nan, as read_airr results in
# null fields being "".
assert _is_false("False")
assert _is_false("false")
assert not _is_false(42)
assert not _is_false(True)
assert not _is_false("true")
assert not _is_false("foobar")
assert not _is_false(np.nan)
assert not _is_false(None)
assert not _is_false("nan")
assert not _is_false("None")
array_test = np.array(
["False", "false", 0, 1, True, False, "true", "Foobar", np.nan, "nan"],
dtype=object,
)
array_test_str = array_test.astype("str")
array_expect = np.array(
[True, True, True, False, False, True, False, False, False, False])
array_test_bool = np.array([True, False, True])
array_expect_bool = np.array([False, True, False])
npt.assert_equal(_is_false(array_test), array_expect)
npt.assert_equal(_is_false(array_test_str), array_expect)
npt.assert_equal(_is_false(pd.Series(array_test)), array_expect)
npt.assert_equal(_is_false(pd.Series(array_test_str)), array_expect)
npt.assert_equal(_is_false(array_test_bool), array_expect_bool)
npt.assert_equal(_is_false(pd.Series(array_test_bool)), array_expect_bool)