SPACEL 1.0.1

SPACEL: characterizing spatial transcriptome architectures by deep-learning

SPACEL: characterizing spatial transcriptome architectures by deep-learning

SPACEL (SPatial Architecture Characterization by dEep Learning) is a Python package of deep-learning-based methods for ST data analysis. SPACEL consists of three modules:

• Spoint embedded a multiple-layer perceptron with a probabilistic model to deconvolute cell type composition for each spot on single ST slice.
• Splane employs a graph convolutional network approach and an adversarial learning algorithm to identify uniform spatial domains that are transcriptomically and spatially coherent across multiple ST slices.
• Scube automatically transforms the spatial coordinate systems of consecutive slices and stacks them together to construct a three-dimensional (3D) alignment of the tissue.

Getting started

• Requirements
• Installation
• Tutorials
  • Spoint tutorial: Deconvolution of cell types distribution of spatial transcriptomics
  • Splane tutorial: Identify uniform spatial domain in multiple slices
  • Scube tutorial: Alignment of multiple spatial transcriptomic slices
  • Scube tutorial: 3D expression modeling with gaussian process regression

Read the documentation for more information.

Requirements

To install SPACEL, you need to install PyTorch with GPU support first. If you don't need GPU acceleration, you can just skip the installation for cudnn and cudatoolkit.

• Create conda environment for SPACEL:

conda env create -f environment.yml

or

conda create -n SPACEL -c conda-forge -c default cudatoolkit=10.2 python=3.8 r-base r-fitdistrplus

You must choose correct PyTorch, cudnn and cudatoolkit version dependent on your graphic driver version.

• Test if PyTorch for GPU available:

python
>>> import torch
>>> torch.cuda.is_available()

If these command line have not return True, please check your gpu driver version and cudatoolkit version. For more detail, look at CUDA Toolkit Major Component Versions.

Note: If you want to run 3D expression GPR model in Scube, you need to install the Open3D python library first.

Installation

• Install SPACEL:

pip install SPACEL