A scalable method to infer fate specific gene regulatory network from single cell gene expression data
conda create --name NetID -c conda-forge -c bioconda r-seurat=4* python=3.10 r-essentials r-base=4.2.0
conda activate NetID # if it encounter the error, run 'source activate' ahead of this code
conda install -c conda-forge r-devtools
pip install geosketch
install.packages("BiocManager")
BiocManager::install("GENIE3")
BiocManager::install("SingleCellExperiment")
devtools::install_github("WWXKenmo/NetID_package")
To speed up installation, user could use conda install mamba at first, then use mamba to install other modules
conda install mamba -c conda-forge
mamba install -c bioconda -c conda-forge cellrank-krylov
## or could use conda to install
## conda install -c bioconda -c conda-forge cellrank-krylov
## install proper version of package
pip install scanpy==1.9.2
pip install matplotlib==3.7
pip install pandas==1.5.3
pip install palantir==1.0.1
pip uninstall numpy
pip install numpy==1.23.5
devtools::install_github("aet21/SCENT")