In Silico Fate Mapping



License BSD-3 PyPI Python Version tests codecov napari hub

Interactive in silico fate mapping from tracking data.

This napari plugin estimates the cell fates from tracking data by building a radial regression model per time point. The user can select an area of interest using a Points layer; the algorithm will advent the probed coordinates forward (or backward) in time, showing the estimated fate.

Video example below:


TODO: add to pypi

You can install in-silico-fate-mapping via pip:

pip install in-silico-fate-mapping

To install the latest development version :

pip install git+

IO file format

This plugin does not depend on a specific file format, the only requirement is using a Track layer from napari.

Despite this, we ship a reader and writer interface. It supports .csv files with the following reader TrackID, t, (z), y, x, z is optional. Such that each tracklet has a unique TrackID and it's composed of a sequence o time and spatial coordinates.

This is extremely similar to how napari store tracks, more information can be found here.

Divisions are not supported at the moment.


If used please cite:



If you encounter any problems, please file an issue along with a detailed description.


  • 0.1.0

Last updated:

  • 27 February 2023

First released:

  • 27 February 2023


  • BSD-3-Clause

Supported data:

  • Information not submitted

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GitHub activity:

  • Stars: 1
  • Forks: 0
  • Issues + PRs: 1

Python versions supported:

Operating system:


  • numpy
  • pandas
  • scikit-learn
  • zarr
  • magicgui
  • qtpy
  • napari
  • click

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