domb-napari
DoMB Tools for napari
A napari plugin offers widgets to analyze fluorescence-labeled proteins redistribution in widefield epifluorescence time-lapse acquisitions. Useful for studying calcium-dependent translocation of neuronal calcium sensors, synaptic receptors traffic during long-term plasticity induction, membrane protein tracking, etc.
Hippocalcin (neuronal calcium sensor) redistributes in dendritic branches upon NMDA application
Widgets
Image Preprocessing
Provides functions for preprocessing multi-channel fluorescence acquisitions:
- If the input image has 4 dimensions (time, channel, x-axis, y-axis), channels will be split into individual 3 dimensions images (time, x-axis, y-axis) with the _ch%index%
suffix.
- If the gaussian blur
option is selected, the image will be blurred with a Gaussian filter using sigma=gaussian sigma
.
- If the photobleaching correction
option is selected, the image will undergo correction with exponential (method exp
) or bi-exponential (method bi_exp
) fitting.
Red-Green Series
Primary method for detecting fluorescent-labeled targets redistribution in time. Returns a series of differential images representing the intensity difference between the current frame and the previous one as new image with the _red-green
suffix.
Parameters:
left frames
- number of previous frames for pixel-wise averaging.space frames
- number of frames between the last left and first right frames.right frames
- number of subsequent frames for pixel-wise averaging.save mask series
- if selected, a series of labels will be created for each frame of the differential image with the thresholdinsertion threshold
.
Up Mask
Generates labels for insertion sites (regions with increasing intensity) based on -red-green
images. Returns labels layer with _up-labels
suffix.
Parameters:
detection img index
- index of the frame from-red-green
image used for insertion sites detection.insertion threshold
- threshold value for insertion site detection, intensity on selected_red-green
frame normalized in -1 - 0 range.save mask
- if selected, a total up mask (containing all ROIs) will be created with the_up-mask
suffix.
Individual Labels Profiles
Builds a plot with mean intensity profiles for each ROI in labels
using absolute intensity (if raw intensity
is selected) or relative intensities (ΔF/F0).
The time scale
sets the number of seconds between frames for x-axis scaling.
The baseline intensity for ΔF/F0 profiles is estimated as the mean intensity of the initial profile points (ΔF win
).
Filters ROIs by minimum (min amplitude
) and maximum (max amplitude
) intensity amplitudes.
Note: Intensity filtering is most relevant for ΔF/F0 profiles.
Additionally, you can save ROI intensity profiles as .csv using the save data frame
option and specifying the saving path
. The output data frames %img_name%_lab_prof.csv
will contain the following columns:
- id - unique image ID, the name of the input
napari.Image
object. - roi - ROI number, consecutively numbered starting from 1.
- int - ROI mean intensity, raw or ΔF/F0 according to the
raw intensity
option. - time - frame time point according to the
time scale
.
Note: The data frame will contain information for all ROIs; filtering options pertain to plotting only.
Labels Profile
Builds a plot with the averaged intensity of all ROIs in labels
. Can take two images (img 0
and img 1
) as input if two profiles
are selected.
The time scale
and ΔF win
are the same as in the Individual Labels Profiles.
The stat method
provides methods for calculating intensity errors:
se
- standard error of mean.iqr
- interquartile range.ci
- 95% confidence interval for t-distribution.