Lineage tree structure
Project description
LineageTree
This library allows to import and work with cell (but not limited to cells) lineage trees. With LineageTree you can read from:
- TGMM algorithm outputs described in Fernando et al. 2014
- TrackMate files described in Tinevez et al. 2017
- MaMuT files described in Wolff et al. 2018
- SVF algorithm outputs described in McDole, Guignard et al. 2018
- ASTEC algorithm outputs described in Guignard, Fiuza et al. 2020
- and few others
Description of the repository
- src: folder containing the package
- setup.py: Installation script
- README.md: This file
- LICENCE: The licence describing file
Basic usage
Once installed the library can be called the following way (as an example):
from LineageTree import lineageTree
and one can then load lineage trees the following way:
For ASTEC data:
lT = lineageTree('path/to/ASTEC.pkl', file_type='ASTEC')
or
lT = lineageTree('path/to/ASTEC.xml', file_type='ASTEC')
For SVF:
lT = lineageTree('path/to/SVF.bin')
For MaMuT:
lT = lineageTree('path/to/MaMuT.xml', file_type='MaMuT')
For TrackMate:
lT = lineageTree('path/to/MaMuT.xml', file_type='TrackMate')
For TGMM:
lT = lineageTree('path/to/single_time_file{t:04d}.xml', tb=0, te=500, file_type='TGMM')
For Mastodon:
lT = lineageTree('path/to/Mastodon.mastodon', file_type='mastodon')
or, for Mastodon csv file:
lT = lineageTree(['path/to/nodes.csv', 'path/to/links.csv'], file_type='mastodon')
Dependencies
Some dependecies are requiered:
- general python dependecies:
- numpy, scipy
- specific dependency:
- svgwrite if svg output is needed
Quick install
To quickly install the library together with its dependencies one can run:
pip install LineageTree
or, for the latest version if you have cloned the directory:
pip install .
or for the latest version wihtout cloning the directory
pip install git+https://github.com/leoguignard/LineageTree
Project details
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