https://github.com/cycelslab/asterquant

Multi aster system quantitative analysis using voronoi tessellation

https://github.com/cycelslab/asterquant

Repository

Multi aster system quantitative analysis using voronoi tessellation

https://github.com/CyCelsLab/AsterQuant/blob/master/

# tesselPacking
The code that relates to work described in Khetan et al. (2021) and a current manuscript in preparation. The code takes in data points and a boundary and outputs tesselations with packing distributions (histograms of polygon frequency).


REFERENCE:
1) Khetan N, Pruliere G, Hebras C, Chenevert J and Athale CA. (2021) Self-organized optimal packing of kinesin-5-driven microtubule asters scales with cell size. J Cell Sci. 134(10):jcs257543. DOI:10.1242/jcs.257543
2) Khetan N, Athale CA. (2022), Tessellation based quantitative framework for the spatial analysis of subcellular structures. Biophys. J. 121, 521a. DOI:10.1016/j.bpj.2021.11.2741


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Following are the step-wise instructions to execute the program.

**Version and Libraries dependencies** 
Please install the following:
1. Python version 3.7.7
2. Numpy 
3. Scipy
4. shapely 
5. pylab  
6. matplotlib

**Usuage for master branch**
Execute the following in the shell command line
> python AsterQuant_V6.py

**Output files** generated in the following folders:


         
         This contains: 
         1. display_Voronoi  >> Data points and Voronoi tessellated image
         2. Overlays_Voronoi >> Overlays above with the raw image if required
         3. RawVoronoi        >> Voronoi image alone
         4. VorStats            >> composite figure ; with plots of histogram of polygonality, NND, area , length distributions and measures such as circularity , eutacticty
         5. VorStatsCorrelation >> continued from #4,



         Main file-names   
         1. AllEutactest.out       >> euctactic measure 
         2. All_NND.out            >> near neighbor distance (NND) for each Voronoi cell
         3. polygonAreaLength.out  >> polygonality, area and lengths of/from each polygons
         4. measures.csv           >> stores all the regularity measures
      


**Scripts**

         1. AsterQuant_V6.py
         2. compute_functions.py
         3. coordinate_merger.py
         4. plot_Quantvoronoi.py
         5. plot_voronoi.py
         6. AsterQuant_V6_B.py.ipynb

**Folder structure**
1. expt                         // These contain input files and images
2. sim                          // These contain input files and images
3. output_fig and               // to store the outputs from a run - IMAGES
4. output_files                 // to store the outputs from a run - MEASURES and ANALYSED DATA
   ( Representative output files and images from phallusia, nematodes and simulations included )

* Make sure "output_fig" and "output_files " exists in the directory 
* Usage:
	USer needs to provide the following inputs - Line # 75 -90 along with the description.
	filenameImage , px2micron , extn , outfilename, u_scale,  method , selectImage , FnameAsterCoor


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Forked from @ https://github.com/khetanneha/AsterQuant


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The work pursued 2017- 2021 shared in 3 branches as explained below:

1. Branch (master) :post-jcs-2021. Updates on the many different measures for analysis and from different systems,  post JCS paper in 2021.

2. Branch: v3_jcs. Parts of the work published in Khetan N, Pruliere G, Hebras C, Chenevert J and Athale CA. (2021) Self-organized optimal packing of kinesin- 5-driven microtubule asters scales with cell size. J Cell Sci. 134(10):jcs257543

3. Branch: AsterQuant. Development until 2021, JCS 
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Please refer to the file: README_AsterQuant.md in this depository for further details.

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