A repository for the freely available software - IVEN (Internal Versus External Neighbourhood quantification). IVEN is a platform that is able to help anlayse biological datasets and interrogate the neighbourhood characteristics of systems. Cells are classified as inside or outside using the convex hull algorithm and subsequently the number of neighbours of cells are calculated using a 'corrected' Delaunay Triangulation.
MATLAB Version:
This version of IVEN includes a more extensive use of GUIs and is generally recommended for intitial use with IVEN (especially if being used by those who are not necessarily familiar with coding). This version has been developed in the 2020 release of MATLAB, with some functions (most notably import of excel file) needing some slight changing to be run in older versions of MATLAB. This current version has been developed using Windows and so some output of files as Excel documents may need to be alterred on a Mac OS, see tutorials. Note: Statistics and Machine Learning toolbox required.
Python 3 Version:
This version includes a simplistic and quicker GUI to aid with cell classification (inside versus outside) but a hard coded approach to select the thresholding of neighbour distances. Any changes to how neighbours are thresholding will have to made as advised in the tutorials.
Tutorials Available:
-Data Assembly for Input into IVEN Pipeline
-IVEN Neighbour Distance Threshold Advice
-IVEN Parameter Change
-IVEN Use in MATLAB
-IVEN Use in Python
-VIDEO: Data Assembly
-VIDEO: MATLAB IVEN
-VIDEO: Python IVEN
-VIDEO: Python Siplay Final Figure
Help in implementing the code:
Contact jessica.forsyth@postgrad.manchester.ac.uk with screenshots and details description of any issues with implementation. Please refer to the videos and video tutorials first for quick help on how to use IVEN.