Neuron density and heatmap analysis tools used for sensory neuron analysis in Integrins protect nociceptive neurons in models of paclitaxel-mediated peripheral sensory neuropathy
doi: https://doi.org/10.1101/829655
Step 1 and 2 (Fiji/ImageJ macros):
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Use 1_Neuron_Density_Heatmap_Creation_Kernel.ijm on a folder containing proprocessed thresholded neuron images
- For each neuron image, the soma will be detected and removed before density calculations are performed on the remaining arbours using the defined area size (e.g. 50 x 50 microns)
- A distance map from the soma is also calculated
- Final output is a image containing 4 channels: 1) soma, 2) density heatmap, 3) neuron, 4) distance map
- ~ 30 seconds / neuron image (2048 x 2048)
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Use 2_Density_Measurements.ijm on the same folder
- This step creates a table for each neuron in a subfolder \Density_plots containing mean and standard deviations of density measurements based on distance from the soma (10 micron bins)
Step 3 (Python Jupyter Notebook):
- Use 3_Density and convex hull summary on the \Density_Heatmap subfolder
- This notebook will generate a histogram for each density image and a summary table for the full dataset (convex hull area, peak density, total pixels with density zero)
