def test_fetch_multiple_subsample():
af = AtlasFetcher()
atlas = af.fetch_multiple_atlases(['Darmanis_2015', 'Enge_2017'],
kind='subsample')
assert (isinstance(atlas, AnnData))
assert ('CellType' in atlas.obs.columns)
assert ('Dataset' in atlas.obs.columns)
def test_fetch_multiple_subsample():
af = AtlasFetcher()
atlas = af.fetch_multiple_atlases(['Darmanis_2015', 'Enge_2017'],
kind='subsample')
assert (isinstance(atlas, dict))
assert ('counts' in atlas)
assert ('cell_types' in atlas)
def test_fetch_Enge_2017():
af = AtlasFetcher()
atlas = af.fetch_atlas('Enge_2017')
assert (isinstance(atlas, AnnData))
assert ('NumberOfCells' in atlas.obs.columns)
counts = atlas[:, ['INS', 'GCG', 'PPY']]
assert (counts['beta', 'INS'].X > counts['acinar', 'INS'].X)
def test_fetch_Enge_2017():
af = AtlasFetcher()
atlas = af.fetch_atlas('Enge_2017')
assert (isinstance(atlas, dict))
assert ('counts' in atlas)
assert ('number_of_cells' in atlas)
counts = atlas['counts'].loc[['INS', 'GCG', 'PPY']]
assert (counts.loc['INS', 'beta'] > counts.loc['INS', 'acinar'])
def test_average_Darmanis_2015():
af = AtlasFetcher()
atlas = af.fetch_atlas('Darmanis_2015', kind='subsample')
ss = average_atlas(
atlas,
)
assert(isinstance(ss, anndata.AnnData))
assert(ss.shape[0] == 8)
def test_run_within_atlas():
aname = 'Darmanis_2015'
atlas = AtlasFetcher().fetch_atlas(aname, kind='subsample')
matrix = atlas.copy()
cell_types = atlas.obs['CellType'].values
sa = Subsample(aname)
sa.fit(matrix)
# Small samples are a bit tricky, one cell can tip the balance
assert ((cell_types == sa.membership).mean() >= 0.85)
def test_run_across_atlas():
atlas = AtlasFetcher().fetch_atlas('Enge_2017', kind='subsample')
matrix = atlas.copy()
cell_types = atlas.obs['CellType'].values
sa = Subsample(
'Baron_2016',
n_pcs=25,
n_features_per_cell_type=3,
n_features_overdispersed=200,
)
sa.fit(matrix)
# Nobody's perfect
# Baron annotates Stellate cells more accurately, so we skip them
assert ((cell_types == sa.membership)[:60].mean() >= 0.5)
def test_run_within_atlas():
aname = 'Darmanis_2015'
atlas = AtlasFetcher().fetch_atlas(aname, kind='subsample')
matrix = atlas['counts']
cell_types = atlas['cell_types'].values
sa = Subsample(aname)
sa.fit(matrix)
# Nobody's perfect
assert ((cell_types == sa.membership).mean() >= 0.9)
def test_run_within_atlas_means():
aname = 'Darmanis_2015'
atlas = AtlasFetcher().fetch_atlas(aname, kind='average')
ind = [0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 4, 5, 6, 0]
matrix = atlas['counts'].iloc[:, ind]
cell_types = atlas['counts'].columns.values[ind]
sa = Subsample(aname)
sa.fit(matrix)
# Nobody's perfect
assert ((cell_types == sa.membership).mean() >= 0.9)
def test_run_mock_cells():
aname = 'Darmanis_2015_nofetal'
atlas = AtlasFetcher().fetch_atlas(aname, kind='average')
ind = [0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 4, 5]
matrix = atlas[ind]
cell_types = atlas.obs_names.values[ind]
sa = Averages(
aname,
n_pcs=10,
)
sa.fit(matrix)
assert ((cell_types == sa.membership).mean() > 0.9)
def test_embed_averages():
aname = 'Darmanis_2015_nofetal'
atlas = AtlasFetcher().fetch_atlas(aname, kind='subsample')
ind = [
0, 2, 5, 8, 10, 15, 20, 25, 28, 30, 35, 38, 40, 45, 50, 60, 70, 75, 80,
90
]
matrix = atlas[ind].copy()
sa = Averages(
aname,
n_features_per_cell_type=2,
n_features_overdispersed=5,
n_pcs=9,
)
sa.fit(matrix)
vs = sa.embed()
assert (vs.shape[1] == 4)
def test_run_within_atlas():
aname = 'Darmanis_2015_nofetal'
atlas = AtlasFetcher().fetch_atlas(aname, kind='subsample')
ind = [
0, 2, 5, 8, 10, 15, 20, 25, 28, 30, 35, 38, 40, 45, 50, 60, 70, 75, 80,
90
]
matrix = atlas[ind]
cell_types = atlas.obs['CellType'].values[ind]
sa = Averages(
aname,
n_features_per_cell_type=2,
n_features_overdispersed=5,
n_pcs=9,
)
sa.fit(matrix)
for i in range(len(cell_types)):
print('{:10s} {:10s}'.format(cell_types[i], sa.membership[i]))
print((cell_types == sa.membership).mean())
assert ((cell_types == sa.membership).mean() >= 0.5)
def test_fetch_multiple():
af = AtlasFetcher()
atlas = af.fetch_multiple_atlases(['Darmanis_2015', 'Enge_2017'])
assert (isinstance(atlas, AnnData))
assert ('NumberOfCells' in atlas.obs.columns)
def test_fetch_Darmanis_2015_subsample():
af = AtlasFetcher()
atlas = af.fetch_atlas('Darmanis_2015', kind='subsample')
assert (isinstance(atlas, AnnData))
assert ('CellType' in atlas.obs.columns)
def test_fetch_Darmanis_2015_subsample():
af = AtlasFetcher()
atlas = af.fetch_atlas('Darmanis_2015', kind='subsample')
assert (isinstance(atlas, dict))
assert ('counts' in atlas)
assert ('cell_types' in atlas)
def test_constructor():
af = AtlasFetcher()
def test_fetch_Darmanis_2015():
af = AtlasFetcher()
atlas = af.fetch_atlas('Darmanis_2015')
assert (isinstance(atlas, dict))
assert ('counts' in atlas)
assert ('number_of_cells' in atlas)
def test_list_atlases():
af = AtlasFetcher()
table = af.list_atlases()
assert (table is not None)
def test_fetch_table():
af = AtlasFetcher()
af.fetch_atlas_table()
assert (af.atlas_table is not None)
def test_fetch_multiple():
af = AtlasFetcher()
atlas = af.fetch_multiple_atlases(['Darmanis_2015', 'Enge_2017'])
assert (isinstance(atlas, dict))
assert ('counts' in atlas)
assert ('number_of_cells' in atlas)
def test_fetch_Darmanis_2015():
af = AtlasFetcher()
atlas = af.fetch_atlas('Darmanis_2015')
assert (isinstance(atlas, AnnData))
assert ('NumberOfCells' in atlas.obs.columns)