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NetID

A scalable method to infer fate specific gene regulatory network from single cell gene expression data

NetID

Tutorial

Tutorial of NetID

Installation

Basic installation

Create conda environment (recommand but not necessary)

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

Install devtools and geosketch

conda install -c conda-forge r-devtools
pip install geosketch

install dependence in R including GENIE3, SingleCellExperiment and NetID (switch to the R terminal)

install.packages("BiocManager")
BiocManager::install("GENIE3")
BiocManager::install("SingleCellExperiment")
devtools::install_github("WWXKenmo/NetID_package")

Advance installation

install cellrank and palantir to realize lineage-specific GRN prediction

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

install cytotrace and scent to determine the root cell

devtools::install_github("aet21/SCENT")

Citation

@article{PUSH:72058,
  author = {Wang, W. and Wang, Y. and Lyu, R. and Gr{\"u}n, D.},
  title = {{Scalable identification of lineage-specific gene regulatory networks from metacells with NetID.}},
  journal = {Genome Biol.},
  location = {Campus, 4 Crinan St, London N1 9xw, England},
  publisher = {Bmc},
  volume = {25},
  number = {1},
  year = {2024},
  issn = {1474-760X},
  eissn = {1465-6906},
}