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 $PATH environment variable. R (v4.0.0 or newer) https://www.r-project.org/ Rsubread (v2.12.2 or newer) http://bioconductor.org/packages/3.16/bioc/html/Rsubread.html CellRanger (v6.0.1) https://support.10xgenomics.com/single-cell-gene-expression/software/overview/welcome STARsolo (v2.7.10a) https://github.com/alexdobin/STAR sra-tools (v2.10.0 or newer) https://github.com/ncbi/sra-tools Seurat (v3.0.0 or newer) https://satijalab.org/seurat/ edgeR (v3.30.0 or newer) https://bioconductor.org/packages/edgeR/ limma (v3.44.0 or newer) https://bioconductor.org/packages/limma/ mltools (v0.3.5 or newer) https://cran.r-project.org/web/packages/mltools/index.html Reference packages generated by 10x Genomics are also required for this analysis and they can be downloaded from the following link (2020-A version for individual human and mouse reference packages should be selected): https://support.10xgenomics.com/single-cell-gene-expression/software/downloads/latest After all these are done, you can simply run the shell script ‘test-all-new.bash’ to perform all the analyses carried out in the paper. This script will automatically download the mixture scRNA-seq data from the SRA database, and it will output a text file called ‘test-all.log’ that contains all the screen outputs and speed/accuracy results of CellRanger, STARsolo and cellCounts.本页面包含复现以下论文成果所需的全部数据与代码： 廖洋（Yang Liao）、迪内什·拉古（Dinesh Raghu）、巴平德·帕尔（Bhupinder Pal）、丽莎·米尔克（Lisa Mielke）以及施伟（Wei Shi）。《cellCounts：10x Chromium单细胞RNA测序数据的快速精准定量》（cellCounts: fast and accurate quantification of 10x Chromium single-cell RNA sequencing data），已投稿待审。 推荐使用运行CentOS 7（或更高版本）或Ubuntu 20.04（或更高版本）操作系统的Linux计算机开展本分析。该计算机需配备至少2 TB磁盘空间与64 GB以上内存。运行分析前需安装以下软件包，安装生成的可执行文件需添加至$PATH环境变量中： R（v4.0.0及更高版本），下载链接：https://www.r-project.org/ Rsubread（v2.12.2及更高版本），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及更高版本），下载链接：https://github.com/ncbi/sra-tools Seurat（v3.0.0及更高版本），下载链接：https://satijalab.org/seurat/ edgeR（v3.30.0及更高版本），下载链接：https://bioconductor.org/packages/edgeR/ limma（v3.44.0及更高版本），下载链接：https://bioconductor.org/packages/limma/ mltools（v0.3.5及更高版本），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，可从以下链接下载（需选择针对人类与小鼠个体的2020-A版本参考包）： https://support.10xgenomics.com/single-cell-gene-expression/software/downloads/latest 完成所有准备工作后，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的所有屏幕输出内容以及运行速度、定量精度结果。