def detect_foci(self, showplot=False):
'''
Clusters that are big enough can be considered foci and could be assigned
as transcription sites in later steps.
Key params:
radius : int
The maximum distance between two samples for one to be considered as
in the neighborhood of the other. Radius expressed in nanometer.
nb_min_spots : int
The number of spots in a neighborhood for a point to be considered as
a core point (from which a cluster is expanded). This includes the
point itself.
'''
self.spots_and_foci, self.foci = detection.detect_foci(
self.spots_post_decomposition, self.voxel_size_z,
self.voxel_size_yx, self.foci_radius, self.nb_in_foci)
if showplot:
plot.plot_detection(
self.rna_mip,
[self.spots_post_decomposition, self.foci[:, :3]],
path_output=f'{self.plotdir}/{self.fov_name}foci',
ext='png',
shape=["circle", "polygon"],
radius=[self.radius_yx, self.radius_yx * 2],
color=["red", "blue"],
linewidth=[1, 2],
fill=[False, True],
framesize=(10, 8),
contrast=True,
show=self.show)
def detect_spots(self):
# sigma
sigma_z, sigma_xy, sigma_xy = detection.get_sigma(self.voxel_size_z,
self.voxel_size_xy,
self.psf_z, self.psf_xy)
sigma = (sigma_z, sigma_xy, sigma_xy)
# LoG filter
rna_log = stack.log_filter(self.rna, sigma)
# local maximum detection
mask = detection.local_maximum_detection(rna_log, min_distance=sigma)
# thresholding
threshold = detection.automated_threshold_setting(rna_log, mask)
spots, _ = detection.spots_thresholding(rna_log, mask, threshold)
#note radius
(radius_z, radius_xy, radius_xy) = detection.get_radius(self.voxel_size_z,
self.voxel_size_xy,
self.psf_z, self.psf_xy)
self.sigma_z = sigma_z
self.sigma_xy = sigma_xy
self.radius_z = radius_z
self.radius_xy = radius_xy
self.threshold = threshold
self.spots = spots
plot.plot_detection(self.rna_mip, self.spots, radius=self.radius_xy,
framesize=(10, 8), contrast=True, show=False,
path_output=f'{self.plotdir}/{self.fov_name}spots',
ext='png')
def decompose_clusters(self, showplot=False):
#Cluster detection: try to decompose clusters of spots into individual foci.
# alpha impacts the number of spots per cluster
# beta impacts the number of detected clusters
self.spots_post_decomposition, self.clusters, self.reference_spot = \
detection.decompose_cluster(self.rna, self.spots, self.voxel_size_z,
self.voxel_size_yx, self.psf_z, self.psf_yx,
alpha=0.7, beta=1)
plot.plot_reference_spot(
self.reference_spot,
path_output=f'{self.plotdir}/{self.fov_name}refspot',
ext='png',
contrast=True,
show=self.show)
if showplot:
plot.plot_detection(
self.rna_mip,
self.spots_post_decomposition,
radius=self.radius_yx,
framesize=(10, 8),
contrast=True,
show=self.show,
path_output=f'{self.plotdir}/{self.fov_name}clusters',
ext='png')
def detect_foci(self):
#Clusters that are big enough can be considered foci
self.spots_post_clustering, self.foci = detection.detect_foci(
self.spots_post_decomposition,
self.voxel_size_z, self.voxel_size_xy,
self.cluster_radius, self.nb_in_cluster)
plot.plot_detection(self.rna_mip, [self.spots_post_decomposition, self.foci[:, :3]],
path_output = f'{self.plotdir}/{self.fov_name}foci',
ext='png', shape=["circle", "polygon"],
radius=[self.radius_xy, self.radius_xy*2],
color=["red", "blue"], linewidth=[1, 2],
fill=[False, True], framesize=(10, 8), contrast=True,
show=False)
def detect_spots(self, showplot=False):
# sigma
sigma_z, sigma_yx, sigma_yx = detection.get_sigma(
self.voxel_size_z, self.voxel_size_yx, self.psf_z, self.psf_yx)
sigma = (sigma_z, sigma_yx, sigma_yx)
# LoG filter
rna_log = stack.log_filter(self.rna, sigma)
# local maximum detection
mask = detection.local_maximum_detection(rna_log, min_distance=sigma)
if self.manual_threshold is not None:
spots, _ = detection.spots_thresholding(rna_log, mask,
self.manual_threshold)
self.threshold = self.manual_threshold
self.threshold_type = 'manual'
else:
# thresholding
threshold = detection.automated_threshold_setting(rna_log, mask)
spots, _ = detection.spots_thresholding(rna_log, mask, threshold)
self.threshold = threshold
self.threshold_type = 'auto'
#note radius
(radius_z, radius_yx,
radius_yx) = detection.get_radius(self.voxel_size_z,
self.voxel_size_yx, self.psf_z,
self.psf_yx)
self.sigma_z = sigma_z
self.sigma_yx = sigma_yx
self.radius_z = radius_z
self.radius_yx = radius_yx
self.rna_log = rna_log
self.mask = mask
self.spots = spots
if showplot:
plot.plot_detection(
self.rna_mip,
self.spots,
radius=self.radius_yx,
framesize=(10, 8),
contrast=True,
show=self.show,
path_output=f'{self.plotdir}/{self.fov_name}spots',
ext='png')