Lineage tree structure for TGMM algorithm
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')
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 .
or
python setup.py install [--user]
Project details
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