Morphomics 2.0.7

morphOMICs: a python package for the topological and statistical analysis of microglia morphology (appliable to any cell structure)

morphOMICs

morphOMICs is a Python package containing tools for analyzing microglia morphology using a topological data analysis approach. Note that this algorithm is designed not only for microglia applications but also for any dynamic branching structures across natural sciences.

• Overview
• Required Dependencies
• Installation Guide
• Usage

Overview

morphOMICs is a topological data analysis approach which combines the Topological Morphology Descriptor (TMD) with bootstrapping approach, dimensionality reduction strategies to visualize microglial morphological signatures and their relationships across different biological conditions.

Required Dependencies

Python : <= 3.10

numpy : 1.8.1+, scipy : 0.13.3+, pickle : 4.0+, enum34 : 1.0.4+, scikit-learn : 0.19.1+, tomli: 2.0.1+, matplotlib : 3.2.0+, ipyvolume: 0.6.1+, umap-learn : 0.3.10+, morphon: 0.0.8+, pylmeasure: 0.2.0+, fa2_modified

Installation Guide

You need Python 3.9 or 3.10 to run this package.

conda create -n morphology python=3.9
conda activate morphology
pip install morphomics

Usage

To run a typical morphOMICs pipeline, create a .toml parameter file (see examples). The parameter file is build such that it modularizes the steps required to generate the phenotypic spectrum. Once you have completed filling up the necessary information in the parameter file, you can use the examples\run.ipynb file to have an idea on how to run this program.