SCDC: Bulk Gene Expression Deconvolution by Multiple Single-Cell RNA Sequencing References

SCDC is a deconvolution method for bulk RNA-seq that leverages cell-type specific gene expressions from multiple scRNA-seq reference datasets. SCDC adopts an ENSEMBLE method to integrate deconvolution results from different scRNA-seq datasets that are produced in different laboratories and at different times, implicitly addressing the batch-effect confounding.

Installation

You can install the released version of SCDC from GitHub with:

if (!require("devtools")) {
  install.packages("devtools")
}
devtools::install_github("meichendong/SCDC")

Vignettes

Please see the vignettes page.

The SCDC paper is published at Briefings In Bioinformatics.

Note of the current repository

This repository is a clone of https://github.com/crhisto/SCDC. It contains the following modifications:

• Compatibility with sparse matrices using: dgCMatrix objects in R.
• Routines with parallelization
• Dynamic threshold for markers selection
• Improvements in logs and so on.

This has been done as part of the project: https://github.com/crhisto/thymus_NPM-ALK_notebook.

If you want to install the SCDC library with these modifications you can use:

if("SCDC" %in% rownames(installed.packages())){
  library(SCDC)
}else{
  devtools::install_github( repo = "crhisto/SCDC")
  library(SCDC)
}

Also, you must use the following libraries with support of sparse matrix (dgCMatrix) for large scRNA-seq datasets:

• Biobase: https://github.com/crhisto/Biobase
• xbioc: https://github.com/crhisto/xbioc