scCDC (single-cell Contamination Detection and Correction)

Developed by Weijian Wang, Yihui Cen, Zezhen Lu

Description

scCDC is a computational algorithm developed to detect global contamination-causing genes (GCGs) in single cell and single nuclei RNA-Seq datasets and perform further decontamination on the GCGs.

Installation

scCDC can be installed from Github with the following code in R:

if(!require("devtools", quietly = TRUE)){
  install.packages("devtools")
}

library(devtools)
install_github("ZJU-UoE-CCW-LAB/scCDC")

The current version of scCDC is developed based on Seurat V4, and we plan to update it to be compatible with Seurat V5 in the near future. Seurat V4 can be installed with the following code in R:

if (!require("remotes", quietly = TRUE)){
    install.packages("remotes")
}

library(remotes)
remotes::install_github("satijalab/seurat", ref="release/4.3.0")

Quick start

If you have a Seurat Object that contains clustering information, the typical scCDC workflow would be:

library(scCDC)
seuratobject = readRDS('/path/to/seuratobject')
GCGs = ContaminationDetection(seuratobject)
contamination_ratio = ContaminationQuantification(seuratobject,rownames(GCGs))
seuratobj_corrected = ContaminationCorrection(seuratobject,rownames(GCGs))
DefaultAssay(seuratobj_corrected) = "Corrected"

The decontaminated count matrix is stored in the 'Corrected' assay in the output Seurat Object, which can be directly used for downstram analysis. If you want to get the decontaminted count matrix, use the following code:

corrected_count_matrix = data.frame(seuratobj_corrected@assays[["Corrected"]]@counts)

If you want to start with count matrix, see vignettes for details.

Usage

For detailed info on scCDC method and applications, please check out the package vignettes, or with the following code in R:

browseVignettes("scCDC")

Contact

Any questions or suggestions on scCDC are welcomed! Please report it on issues, or contact Weijian Wang (weijianwang@ucla.edu), Yihui Cen (yihuicen@g.ucla.edu) or Zezhen Lu (12307092@zju.edu.cn).

Reference

Wang, W., Cen, Y., Lu, Z., Xu, Y., Sun, T., Xiao, Y., Liu, W., Li, J. J., & Wang, C. (2024). scCDC: a computational method for gene-specific contamination detection and correction in single-cell and single-nucleus RNA-seq data. Genome biology, 25(1), 136. https://doi.org/10.1186/s13059-024-03284-w

ZJU-UoE-CCW-LAB / scCDC

readme