https://github.com/liuy12/scdeconr
Deconvolution of bulk RNA-seq data using single-cell RNA-seq data as reference
https://github.com/liuy12/scdeconr
bulk-rna-seq-deconvolution deconvolution differential-expression ffpe geneset-enrichment-analysis r scdeconr single-cell
Last synced: 5 months ago
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Deconvolution of bulk RNA-seq data using single-cell RNA-seq data as reference
- Host: GitHub
- URL: https://github.com/liuy12/scdeconr
- Owner: Liuy12
- License: gpl-3.0
- Created: 2023-04-07T03:07:29.000Z (almost 3 years ago)
- Default Branch: master
- Last Pushed: 2025-07-14T16:11:36.000Z (8 months ago)
- Last Synced: 2025-09-24T10:57:37.905Z (6 months ago)
- Topics: bulk-rna-seq-deconvolution, deconvolution, differential-expression, ffpe, geneset-enrichment-analysis, r, scdeconr, single-cell
- Language: HTML
- Homepage: https://liuy12.github.io/SCdeconR/
- Size: 38.8 MB
- Stars: 6
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: NEWS.md
- License: LICENSE.md
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README
# 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
``` r
# install devtools if it's not installed already
if (!require("devtools", quietly = TRUE)) install.packages("devtools")
devtools::install_github("liuy12/SCdeconR")
```
To use [scaden](https://github.com/KevinMenden/scaden) within SCdeconR, follow the below steps:
```r
# 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.
``` r
# 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
```r
library(SCdeconR)
```
See [here](https://liuy12.github.io/SCdeconR/) for detailed documentation and tutorials.
See [here](https://htmlpreview.github.io/?https://github.com/Liuy12/SCdeconR/blob/master/inst/reprod_doc/Reproducible_document.html) for a document to reproduce the results from the study.