In Silico Fate Mapping

in-silico-fate-mapping

TODO

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:

Installation

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+https://github.com/royerlab/in-silico-fate-mapping.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.

Citing

If used please cite:

TBD

Issues

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

Version:

  • 0.1.0

Last updated:

  • 27 February 2023

First released:

  • 27 February 2023

License:

  • BSD-3-Clause

Supported data:

  • Information not submitted

Open extension:

Save extension:

Save layers:

GitHub activity:

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

Python versions supported:

Operating system:

Requirements:

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

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