GitHub - Liuy12/SCdeconR: Deconvolution of bulk RNA-seq data using single-cell RNA-seq data as reference (original) (raw)
SCdeconR
SCdeconR aims to provide a streamlined workflow from deconvolution of bulk RNA-seq data to downstream differential and gene-set enrichment analysis. SCdeconR provides a simulation framework to generate artificial bulk samples for benchmarking purposes. It also provides various visualization options to compare the influence of adjusting for cell-proportions differences on differential expression and pathway analyses.
Installation
install devtools if it's not installed already
if (!require("devtools", quietly = TRUE)) install.packages("devtools") devtools::install_github("liuy12/SCdeconR")
To use scaden within SCdeconR, follow the below steps:
install reticulate package first
install.packages("reticulate")
Intall scaden python package:
Use pip:
pip install scaden
Or use Conda:
conda install scaden
Then provide your desired python path (that have scaden installed) to option pythonpath
for function scdecon
. You should be good to go.
The following packages are optional, and only needed for specific methods within SCdeconR.
install BiocManager if it's not installed already
if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager")
data normalization
scater
BiocManager::install("scater")
scran
BiocManager::install("scran")
Linnorm
BiocManager::install("Linnorm")
SingleCellExperiment
BiocManager::install("SingleCellExperiment")
deconvolution methods
FARDEEP
install.packages("FARDEEP")
nnls
install.packages("nnls")
MuSiC
devtools::install_github('xuranw/MuSiC')
SCDC
devtools::install_github("meichendong/SCDC")
differential expression
DESeq2
BiocManager::install("DESeq2")
cell-type specific gene expression
spacexr
devtools::install_github("dmcable/spacexr", build_vignettes = FALSE)
interactive plot
install.packages("plotly")
Usage
See here for detailed documentation and tutorials.
See here for a document to reproduce the results from the study.