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")

Hint: 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 a formerly available version manually from its archive. Besides, if you encounter errors saying package SoupX is unavalibale, you can refer to its GitHub and install it via

devtools::install_github("constantAmateur/SoupX")

The vignette of scCancer can be found in this page or the project wiki.

We provide an example data of kidney cancer from 10X Genomics, and following are the generated HTML reports:

• report-scStat.html
• report-scAnno.html

For multi-datasets, following is a generated HTML report for three kidney cancer samples integration analysis:

• report-scAnnoComb.html

Please use the following citation:

Wenbo Guo, Dongfang Wang, Shicheng Wang, Yiran Shan, Jin Gu. 2019. bioRxiv doi: https://doi.org/10.1101/800490

GPL-3