cellCounts

This page includes the data and code necessary to reproduce the results of the following paper:
Yang Liao, Dinesh Raghu, Bhupinder Pal, Lisa Mielke and Wei Shi. cellCounts: fast and accurate quantification of 10x Chromium single-cell RNA sequencing data. Under review.
A Linux computer running an operating system of CentOS 7 (or later) or Ubuntu 20.04 (or later) is recommended for running this analysis. The computer should have >2 TB of disk space and >64 GB of RAM. The following software packages need to be installed before running the analysis. Software executables generated after installation should be included in the $PATH environment variable.

R (v4.0.0 or newer)  https://www.r-project.org/
Rsubread (v2.12.2 or newer) http://bioconductor.org/packages/3.16/bioc/html/Rsubread.html
CellRanger (v6.0.1) https://support.10xgenomics.com/single-cell-gene-expression/software/overview/welcome
STARsolo (v2.7.10a) https://github.com/alexdobin/STAR
sra-tools (v2.10.0 or newer) https://github.com/ncbi/sra-tools
Seurat (v3.0.0 or newer) https://satijalab.org/seurat/
edgeR (v3.30.0 or newer)  https://bioconductor.org/packages/edgeR/
limma (v3.44.0 or newer)  https://bioconductor.org/packages/limma/
mltools (v0.3.5 or newer) https://cran.r-project.org/web/packages/mltools/index.html

Reference packages generated by 10x Genomics are also required for this analysis and they can be downloaded from the following link (2020-A version for individual human and mouse reference packages should be selected):
https://support.10xgenomics.com/single-cell-gene-expression/software/downloads/latest
After all these are done, you can simply run the shell script ‘test-all-new.bash’ to perform all the analyses carried out in the paper. This script will automatically download the mixture scRNA-seq data from the SRA database, and it will output a text file called ‘test-all.log’ that contains all the screen outputs and speed/accuracy results of CellRanger, STARsolo and cellCounts.

本页面包含复现下述论文成果所需的全部数据与代码：
Yang Liao、Dinesh Raghu、Bhupinder Pal、Lisa Mielke与Wei Shi. cellCounts: 10x Chromium单细胞RNA测序数据的快速精准定量分析，目前处于投稿评审阶段。

本分析推荐运行于搭载CentOS 7（或更高版本）或Ubuntu 20.04（或更高版本）操作系统的Linux计算机，该计算机需具备至少2TB磁盘空间与64GB以上内存。运行本分析前需安装以下软件包，且安装后生成的可执行文件需添加至$PATH环境变量中：
- R（v4.0.0及以上版本），下载链接：https://www.r-project.org/
- Rsubread（v2.12.2及以上版本），下载链接：http://bioconductor.org/packages/3.16/bioc/html/Rsubread.html
- CellRanger（v6.0.1），下载链接：https://support.10xgenomics.com/single-cell-gene-expression/software/overview/welcome
- STARsolo（v2.7.10a），下载链接：https://github.com/alexdobin/STAR
- sra-tools（v2.10.0及以上版本），下载链接：https://github.com/ncbi/sra-tools
- Seurat（v3.0.0及以上版本），下载链接：https://satijalab.org/seurat/
- edgeR（v3.30.0及以上版本），下载链接：https://bioconductor.org/packages/edgeR/
- limma（v3.44.0及以上版本），下载链接：https://bioconductor.org/packages/limma/
- mltools（v0.3.5及以上版本），下载链接：https://cran.r-project.org/web/packages/mltools/index.html

本分析还需使用10x Genomics生成的参考数据集，可通过下述链接下载（针对人类与小鼠的参考数据集应选择2020-A版本）：
https://support.10xgenomics.com/single-cell-gene-expression/software/downloads/latest

完成上述所有配置后，仅需运行shell脚本`test-all-new.bash`即可复现论文中的全部分析流程。该脚本将自动从SRA（Sequence Read Archive）数据库下载混合单细胞RNA测序（single-cell RNA sequencing, scRNA-seq）数据，并输出名为`test-all.log`的文本文件，其中包含CellRanger、STARsolo与cellCounts的全部屏幕输出信息以及运行速度与准确率结果。