/AsterQuant

Multi aster system quantitative analysis using voronoi tessellation

Primary LanguageJupyter NotebookGNU General Public License v3.0GPL-3.0

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

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:

<output_fig>

     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,

<output_files>

     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

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


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


Please refer to the file: README_AsterQuant.md in this depository for further details.