The scCancer
package focuses on processing and analyzing droplet-based scRNA-seq data for cancer research. Except basic data processing steps, this package takes several special considerations for cancer-specific features.
The workflow of scCancer
mainly consists of three modules: scStatistics
, scAnnotation
, and scCombination
.
- The
scStatistics
performs basic statistical analyses of raw data and quality control. - The
scAnnotation
performs functional data analyses and visualizations, such as low dimensional representation, clustering, cell type classification, cell malignancy estimation, cellular phenotype analyses, gene signature analyses, cell-cell interaction analyses, etc. - The
scCombination
perform multiple samples data integration, batch effect correction and analyses visualization.
After the computational analyses, detailed and graphical reports were generated in user-friendly HTML format.
(Click to view larger workflow picture)
- R version: >= 3.5.0
Firstly, please install or update the package devtools
by running
install.packages("devtools")
Then the scCancer
can be installed via
library(devtools)
devtools::install_github("wguo-research/scCancer")
- A dependent package
NNLM
was removed from the CRAN repository recently, so an error about it may be reported during the installation. If so, you can install its a formerly available version by following codes or install manually from its archive.
install.packages("RcppArmadillo")
install.packages("RcppProgress")
install.packages('http://lifeome.net/software/sccancer/packages/NNLM_0.4.3.tar.gz', type='source')
- Some dependent packages on GitHub (as follows) may not be able to install automatically, if you encounter such errors, please refer to their GitHub and install them via corresponding commands.
SoupX
:devtools::install_github("constantAmateur/SoupX")
harmony
:devtools::install_github("immunogenomics/harmony")
liger
:devtools::install_github("MacoskoLab/liger")
The vignette of scCancer
can be found in the project wiki.
We provide an example data of kidney cancer from 10X Genomics, and following are the generated HTML reports:
For multi-datasets, following is a generated HTML report for three kidney cancer samples integration analysis:
Please use the following citation:
Wenbo Guo, Dongfang Wang, Shicheng Wang, Yiran Shan, Changyi Liu, Jin Gu, scCancer: a package for automated processing of single-cell RNA-seq data in cancer, Briefings in Bioinformatics, bbaa127, https://doi.org/10.1093/bib/bbaa127
GPL-3