R Data Package for "TP53 mutations and TET2 deficiency cooperate to drive leukemogenesis and establish an immunosuppressive environment"

This is an R Data Package with processed data necessary to reproduce the R-based scRNA-seq figures from the manuscript entitled "TP53 mutations and TET2 deficiency cooperate to drive leukemogenesis and establish an immunosuppressive environment".Steps to reproduce selected figures:System RequirementsR v4.4RstudioThis software has been tested on Linux Ubuntu 22.04.5Loading the complete dataset occupies approximately 8 GB memory.<br>2. Installationdownload this object in a convenient location on your system.clone the analysis project to your computer using git clone https://github.com/blaserlab/lapalombella_pu.gitopen the R projecta list of the packages required for the project can be found in library_catalogs/blas02_lapalombella_pu.tsv. Filter for packages with status == "active". Install these packages and their dependencies.install custom packages from our R Universe repository using these commands:install.packages('blaseRtools', repos = c('https://blaserlab.r-universe.dev', 'https://cloud.r-project.org'))install.packages('blaseRtemplates', repos = c('https://blaserlab.r-universe.dev', 'https://cloud.r-project.org'))install.packages('blaseRdata', repos = c('https://blaserlab.r-universe.dev', 'https://cloud.r-project.org'))source R/dependencies.R (the final line in that file must be edited to point to the directory containing the data package)source R/configs.R (the file paths defining the output variables should be customized for your system)see the named files in R/ to reproduce specific figures from the manuscripttypical time required for the first installation and data loading is approximately 15 minutes. This excludes the time required to download the data package.

本数据集为R语言数据包，包含复现题为《TP53突变与TET2缺陷协同驱动白血病发生并建立免疫抑制微环境》的论文中基于R语言的单细胞RNA测序（single-cell RNA sequencing, scRNA-seq）图表所需的预处理后数据。

图表复现流程如下：

一、系统需求
R v4.4、Rstudio
本软件已在Linux Ubuntu 22.04.5操作系统中完成兼容性测试。加载完整数据集约占用8 GB内存。

二、安装步骤
1. 将本数据对象下载至系统内的便捷路径中。
2. 通过git clone命令克隆分析项目至本地：git clone https://github.com/blaserlab/lapalombella_pu.git
3. 打开该R语言项目。
4. 项目所需的软件包清单可在library_catalogs/blas02_lapalombella_pu.tsv文件中查阅，筛选出状态为"active"的软件包，并安装这些包及其依赖项。
5. 通过以下命令从本团队的R宇宙仓库安装自定义软件包：
install.packages('blaseRtools', repos = c('https://blaserlab.r-universe.dev', 'https://cloud.r-project.org'))
install.packages('blaseRtemplates', repos = c('https://blaserlab.r-universe.dev', 'https://cloud.r-project.org'))
install.packages('blaseRdata', repos = c('https://blaserlab.r-universe.dev', 'https://cloud.r-project.org'))
6. 执行source R/dependencies.R（需编辑该文件的最后一行，使其指向存储本数据包的目录）。
7. 执行source R/configs.R（需根据您的本地系统自定义定义输出变量的文件路径）。
8. 可参考R/目录下的对应文件，复现论文中的特定图表。

首次完成安装与数据加载的典型耗时约为15分钟，该时长不包含下载本数据包所需的时间。