SpaGFT: Graph Fourier transform for spatial omics representation and analyses of complex organs

Functional tissue unit (FTU) is a spatially organized tissue region and executes specialized biological functions, recurring and varying at different tissue sites. However, the computational identification of FTUs poses challenges due to their convoluted biological functions, poorly-defined molecular features, and varying spatially organized patterns. Here, we present a hypothesis-free graph Fourier transform model, SpaGFT, to represent spatially organized features using the Fourier coefficients, leading to an accurate representation of spatially variable genes and proteins and the characterization of FTU at a fast computational speed. We implemented sequencing-based and imaging-based spatial transcriptomics, spatial-CITE-seq, and spatial proteomics to identify spatially variable genes and proteins, define FTU identities, and infer convoluted functions among FTUs in mouse brains and human lymph nodes. We collected a human tonsil sample and performed CODEX to accurately demonstrate molecular and cellular variability within the secondary follicle structure. The superior accuracy, scalability, and interpretability of SpaGFT indicate that it is an effective representation of spatially-resolved omics data and an essential tool for bringing new insights into molecular tissue biology.

System Requirments

Hardware Requirements

SpaGFT is friendly to hardware. All functions in SpaGFT need the minimum requirements of a CPU with 4 cores and 4G RAM. For large datasets, a large RAM is required to avoid memory overflow.

OS requirements

SpaGFT can run on Windows, Linux, Mac os. The package has been tested on the following systems:

• Linux: Ubuntu 20.04 (recommend)
• Windows: Windows 10

Python Dependencies

SpaGFT requires python version >= 3.7.

kneed==0.7.0
louvain==0.7.1
leidenalg==0.8.10
matplotlib==3.5.2
networkx==2.8
numba==0.55.1
numpy==1.21.5
pandas==1.4.2
plotnine==0.8.0
scanpy==1.9.1
scikit-learn==1.0.2
scipy==1.8.0
gseapy==0.10.8
igraph==0.9.10
chardet==5.1.0
charset-normalizer==3.1.0

Installation Guide

Create a virtual environment

The virtual environment is recommended before installing SpaGFT. Users can install anaconda by following this tutorial. [https://www.anaconda.com/]

If users do not have conda please install Miniconda first:

cd /path/to/software
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh

Create a separated virtual environment

conda create -n spagft_env python==3.8.0
conda activate spagft_env

If users want to quit this virtual environment, just run conda deactivate

Install SpaGFT

Approach 1: Install from PyPI

pip install SpaGFT

Approach 2: Install from source

Before installing SpaGFT formally, the dependency packages should be installed.

Users can install all dependencies by:

git clone https://github.com/OSU-BMBL/SpaGFT
cd SpaGFT
pip install -r requirements.txt

Next, run

python setup.py install

Install jupyter (optional)

Note that we recommend jupyter for interactive usage. It can be installed and configured by

conda install jupyter
python -m ipykernel install --user --name=spagft_env --display-name=spagft_env

Usage and Tutorials

The tutorial of SpaGFT can be found here.