MorphOMICs

❗WARNING❗
These codes contain outdated scripts for running morphOMICs, but will still remain public for legacy reasons. The latest codes are found in https://github.com/siegert-lab/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 novel 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 : 3.7+

numpy : 1.8.1+, scipy : 0.13.3+, pickle : 4.0+, enum34 : 1.0.4+, scikit-learn : 0.19.1+, matplotlib : 3.2.0+

Additional dependencies: anndata : 0.7+, umap-learn : 0.3.10+, palantir : 1.0.0+, fa2

Installation Guide

git clone https://github.com/siegert-lab/MorphOMICs.git
cd morphomics
python3 setup.py install

Usage

The easiest way to navigate through MorphOMICs is to run the Morphomics_demo notebook:

• download demo.zip from https://seafile.ist.ac.at/f/eb13e707041749269ff9/?dl=1
• unzip demo.zip
• cd demo
• jupyter notebook
• Copy the url it generates, it looks something like this: http://127.0.0.1:8888/?token=a4d016c37e162499e17b2993e69073fac0018bd9a779b762
• Open it in your browser
• Then open Morphomics_demo.ipynb