SpaDecon: cell-type deconvolution in spatial transcriptomics with semi-supervised learning

Kyle Coleman, Jian Hu, Amelia Schroeder, Edward B. Lee, Mingyao Li*

SpaDecon is a semi-supervised learning-based method developed to perform cell-type deconvolution on spatially resolved transcriptomics (SRT) datasets. SpaDecon has been shown to provide accurate cell-type deconvolution results for both Spatial Transcriptomics (ST) and 10X Visium SRT datasets. Annotated scRNA-seq gene expression data from the same type of tissue as the SRT data are required for deconvolution.

SpaDecon Installation

• SpaDecon installation requires python version 3.7. The version of python can be checked by:

  import platform
  platform.python_version()

  '3.7.11'

We recommend creating and activating a new conda environment when installing the SpaDecon package. For instance,

conda create -n SpaDecon python=3.7
conda activate SpaDecon

There are mulitple ways to install SpaDecon:

• Install SpaDecon using PyPI:

pip3 install SpaDecon   

• Download and install SpaDecon package from GitHub:

git clone https://github.com/kpcoleman/SpaDecon
cd SpaDecon/
python3 setup.py install --user

Tutorial

A markdown tutorial file can be found here: https://github.com/kpcoleman/SpaDecon/blob/main/tutorial/Tutorial.md

A tutorial in the form of a jupyter notebook can be found here: https://github.com/kpcoleman/SpaDecon/blob/main/tutorial/tutorial.ipynb

Software Requirements

python==3.7
keras==2.2.4
pandas==1.2.4
numpy==1.20.1
scipy==1.6.2
scanpy==1.7.0
anndata==0.7.6
sklearn
tensorflow==1.14.0