def test_compute_normalised_quadrant_densities_protein(self):
image_set = ImageSet(self.repo, path_list=['protein/arhgdia/2h/'])
res = image_set.compute_normalised_quadrant_densities()
mtoc_density = res[res[:, 1] == 1].sum() / len(res[res[:, 1] == 1])
non_mtoc_density = res[res[:, 1] == 0].sum() / len(res[res[:, 1] == 0])
self.assertAlmostEqual(mtoc_density, 1.98375276421, places=3)
self.assertAlmostEqual(non_mtoc_density, 1.0445809579196, places=3)
def test_compute_normalised_quadrant_densities_mrna(self):
image_set = ImageSet(self.repo, path_list=['mrna/arhgdia/2h/'])
res = image_set.compute_normalised_quadrant_densities()
self.assertEqual(res.shape[0], 20)
mtoc_density = res[res[:, 1] == 1].sum() / len(res[res[:, 1] == 1])
self.assertAlmostEqual(mtoc_density, 2.22758047513, places=5)
non_mtoc_density = res[res[:, 1] == 0].sum() / len(res[res[:, 1] == 0])
self.assertAlmostEqual(non_mtoc_density, 1.089256691215, places=5)
def test_compute_normalized_quadrant_densities_protein(self):
image_set = ImageSet(self.repo, path_list=['protein/arhgdia/3h/'])
result1 = image_set.compute_normalised_quadrant_densities(quadrants_num=8)
num_images = image_set.__sizeof__()
self.assertEqual(num_images, image_set.__sizeof__())
self.assertAlmostEqual(result1[result1[:, 1] == 1][:, 0].sum() / num_images,
1.098770606, places=5) # MTOC quadrant density
self.assertAlmostEqual(result1[result1[:, 1] == 0][:, 0].sum() / (num_images * 7),
0.865466580, places=5) # non MTOC quadtant density
result2 = image_set.compute_normalised_quadrant_densities(quadrants_num=8, stripes=3, stripes_flag=True)
self.assertAlmostEqual(result2[result2[:, 1] == 1][:, 0].sum() / (3 * num_images),
0.9803183396, places=5) # MTOC quadrant density
self.assertAlmostEqual(result2[result2[:, 1] == 0][:, 0].sum() / (num_images * 7 * 3),
0.6801687989, places=5) # non MTOC quadtant density
result3 = image_set.compute_normalised_quadrant_densities(quadrants_num=8, peripheral_flag=True,
stripes=3, stripes_flag=True)
self.assertAlmostEqual(result3[result3[:, 1] == 1][:, 0].sum() / (3 * num_images),
0.126123087, places=5) # MTOC quadrant density
self.assertAlmostEqual(result3[result3[:, 1] == 0][:, 0].sum() / (num_images * 7 * 3),
0.011356787, places=5) # non MTOC quadtant density
def test_compute_normalized_quadrant_densities_mrna(self):
image_set = ImageSet(self.repo, path_list=['mrna/arhgdia/2h/'])
result1 = image_set.compute_normalised_quadrant_densities(quadrants_num=8)
num_images = image_set.__sizeof__()
self.assertEqual(num_images, image_set.__sizeof__())
self.assertAlmostEqual(result1[result1[:, 1] == 1][:, 0].sum() / num_images,
1.0780173273, places=5) # MTOC quadrant density
self.assertAlmostEqual(result1[result1[:, 1] == 0][:, 0].sum() / (num_images * 7),
1.1263246459, places=5) # non MTOC quadrant density
result2 = image_set.compute_normalised_quadrant_densities(quadrants_num=8, stripes=3, stripes_flag=True)
self.assertAlmostEqual(result2[result2[:, 1] == 1][:, 0].sum() / (3 * num_images),
1.0225376792, places=5) # MTOC quadrant density
self.assertAlmostEqual(result2[result2[:, 1] == 0][:, 0].sum() / (num_images * 7 * 3),
1.08160649427, places=5) # non MTOC quadrant density
result3 = image_set.compute_normalised_quadrant_densities(quadrants_num=8, peripheral_flag=True,
stripes=3, stripes_flag=True)
self.assertAlmostEqual(result3[result3[:, 1] == 1][:, 0].sum() / (3 * num_images),
0.79154809935, places=5) # MTOC quadrant density
self.assertAlmostEqual(result3[result3[:, 1] == 0][:, 0].sum() / (num_images * 7 * 3),
0.59408432134, places=5) # non MTOC quadrant density
def compute_relative_densities(analysis_repo,
molecule_type,
quadrants_num=4,
peripheral_flag=False):
densities = {}
stripes = constants.analysis_config['STRIPE_NUM']
if peripheral_flag:
stripes_flag = False
stripes = 1
else:
stripes_flag = True
if molecule_type == 'mrna':
timepoints = constants.dataset_config['TIMEPOINTS_MRNA']
else:
timepoints = constants.dataset_config['TIMEPOINTS_PROTEIN']
for gene in constants.analysis_config['PROTEINS']:
median_densities, gene_clusters = [], []
for timepoint in timepoints:
image_set = ImageSet(
analysis_repo,
[molecule_type + "/{0}/{1}/".format(gene, timepoint)])
arr = image_set.compute_normalised_quadrant_densities(
quadrants_num=quadrants_num,
peripheral_flag=peripheral_flag,
stripes=stripes,
stripes_flag=stripes_flag)
num_images = arr.shape[0] // (quadrants_num * stripes)
aligned_densities = arr[:, 0].reshape(num_images,
quadrants_num * stripes)
median_densities_per_slice = np.nanmedian(aligned_densities,
axis=0)
median_densities.append(median_densities_per_slice)
densities[gene] = median_densities
return densities
def compute_density_per_quadrant(analysis_repo,
molecule_type,
groupby_key,
quadrants_num,
quadrant_labels,
molecule_list,
time_points,
mpi_sample_size,
peripheral_flag=False):
assert len(quadrant_labels) == quadrants_num - 1
density_per_quadrant = []
for molecule in molecule_list:
for timepoint in time_points:
density_statictics = {}
image_set = ImageSet(analysis_repo,
[f"{molecule_type}/{molecule}/{timepoint}/"])
if len(image_set.images) < 5:
logger.warning("Image set is small for {}", molecule)
res = image_set.compute_normalised_quadrant_densities(
quadrants_num=quadrants_num, peripheral_flag=peripheral_flag)
mtoc_quadrants = res[res[:, 1] == 1][:, 0]
num_images = res.shape[0] // quadrants_num
non_mtoc_quadrants = res[res[:, 1] == 0][:, 0].reshape(
num_images, quadrants_num - 1)
density_statictics["Gene"] = [molecule] * num_images
density_statictics["Timepoint"] = [timepoint] * num_images
density_statictics["MTOC"] = mtoc_quadrants
for i in range(0, quadrants_num - 1):
density_statictics["Non MTOC" + str(i)] = non_mtoc_quadrants[:,
i]
density_per_quadrant.append(pd.DataFrame(density_statictics))
return DensityStats(df=pd.concat(density_per_quadrant),
group_key=groupby_key,
mpi_sample_size=mpi_sample_size,
quadrant_labels=quadrant_labels,
mtoc_quadrant_label='MTOC')
