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MorphOMICs

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.

Install / Use

/learn @siegert-lab/MorphOMICs
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

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

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

This project relies on a range of scientific computing and machine learning libraries to facilitate data analysis, visualization, and modeling. Key dependencies include NumPy, Pandas, and SciPy for numerical computations, scikit-learn for machine learning, and torch alongside torch-geometric for deep learning applications. Additionally, Matplotlib and UMAP-learn support data visualization and dimensionality reduction, while NetworkX aids in graph-based analyses. The project also integrates H5Py for handling HDF5 files and WandB for experiment tracking. Ensure all dependencies are installed to guarantee full functionality.

Installation Guide

Clone the Repository:

git clone git@github.com:siegert-lab/morphOMICs.git
cd morphOMICs

You need Python 3.9 to run this package. You can install morphOMICs using either Conda or pip. Follow the steps below based on your preferred package manager.

Using Conda

  1. Create and Activate the Conda Environment:
    conda env create -f environment.yml
    conda activate morphomics_env

  2. Install the Package:
    pip install -e .

Using pip

  1. Create and Activate the Virtual Environment:
    python -m venv morphomics_env
    On macOS/Linux:
    source morphomics_env/bin/activate
    On Windows:
    morphomics_env\Scripts\activate

  2. Install the Required Packages:
    pip install -r requirements.txt
    pip install -e .

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.

Related Skills

View on GitHub
GitHub Stars6
CategoryData
Updated5mo ago
Forks5

Languages

Python

Security Score

82/100

Audited on Oct 22, 2025

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