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fishfeats

fishfeats

Topics: rnaFish Epithelium nucleus segm...

Fish&Feats snap

Usage

You can launch fishfeats in Napari by going to Plugins>fishfeats>Start. It will open a file dialog box asking you to select the image that you want to analyze.

Then the image will be displayed, with the different channels shown as separated layers on the left panel.

All the outputs of fishfeats will be saved in the folder called results that will be automatically created in the folder containing your image. If you run fishfeats again on the same image, the program will look into that folder for already saved files, so that you can load previous files and don't have to redo all the steps from scratch.

fishfeats proposes several analyses steps in the main interface:

  • Image scalings: set the global parameter of the image to analyse (scalings, channels)
  • Get junctions: segment/load/correct the cell apical contours in 2D
  • Load junctions from default file: directly load the file containing the segmented cells and create the corresponding cells.
  • Get nuclei: segment/load/correct the nuclei in 3D.
  • Separate junctions and nuclei: if the junctions staining and nuclei staining are in the same channel, to segment them it is necessary to separate them before with this step.
  • Get RNAs: segment/assign/correct/measure the RNAs in one or more RNA channel.
  • Classify cells: manually classify the segmented cells with a user defined criteria (eg "PCNA or not"). Can be automatically prefilled then manually corrected.
  • Measure cytoplasmic staining to measure the intensity of one or more channels in each segmented cell around the surface.

main

When you open a new image, the plugin will directly go to the first mandatory steps of fixing the image scales and channels (image scalings).

Hierarchical clustering

You can launch this analysis with Plugins>fishfeats>Hierarchical clustering. It will perform hierarchical clustering on a set of columns (that contains RNA counts for example) and show the resulting clustering on the segmented cells. See Hierarchical clustering for more infos.

Issues

A list of encountered errors and their solution is given here