CellFreeGMF 0.0.3

cfRNA

CellFreeGMF v0.0.3

Overview

we developed CellFreeGMF, an open-source Python package to identify cfRNA biomarkers and analyze the functional alterations in their originating cells. CellFreeGMF not only enables diagnostic classification of disease samples and identification of cfRNA biomarkers but also elucidate the functional alterations of cfRNA source cells based on cell-free transcriptome and single-cell sequencing data.

Getting started

See Documentation and Tutorials.

Installation

1.1 Software dependencies

scanpy
pytorch
pyG
rpy2

The use of the mclust algorithm requires the rpy2 package and the mclust package. See https://pypi.org/project/rpy2/ for detail.

1.2 PyPI: Directly install the package from PyPI.

pip3 install CellFreeGMF
#Note: you need to make sure that the pip is for python3，or we should install CellFreeGMF by
python3 -m pip install CellFreeGMF
pip3 install CellFreeGMF
#If you do not have permission (when you get a permission denied error), you should install CellFreeGMF by
pip3 install --user CellFreeGMF

1.3 Github

Download the package from Github (https://github.com//zwx94//CellFreeGMF) and install it locally:

cd CellFreeGMF-main
python setup.py build
python setup.py install

1.4 Anaconda

If you do not have Python3.5 or Python3.6 installed, consider installing Anaconda (see Installing Anaconda). After installing Anaconda, you can create a new environment, for example, CellFreeGMF (you can change to any name you like).

#create an environment called CellFreeGMF
conda create -n CellFreeGMF python=3.10
#activate your environment
conda activate CellFreeGMF
git clone https://github.com//zwx94//CellFreeGMF
cd CellFreeGMF
python3 setup.py build
python3 setup.py install
conda deactivate

Citation

Wenxiang Zhang, et al. "From Cell-Free Transcriptomes to Single-Cell Landscapes: Biomarker Discovery and Originating Cell Alteration Analysis via Graph Matrix Factorization." Submitted.