ChromSCape_scChIP_scATAC_compiled_datasets

This folder contains three analysis of one scChIP-seq and one scATAC-seq datasets for the purpose of being visualised by ChromSCape (https://github.com/vallotlab/ChromSCape). <b><br></b><b>Datasets</b><br><b><br></b><b>H3K27me3 scChIP-seq datasets:</b>The samples correspond to mouse cells from patient-derived xenograft (PDX) originating from two different human donors (Grosselin et al., 2019). Raw FASTQ reads were processed using the latest version of our scChIP-seq data engineering pipeline that allowed a more precise removal of PCR and RT duplicates (code available at https://github.com/vallotlab/scChIPseq_DataEngineering) to produce 50kbp binned count matrices given as input to ChromSCape (matrices available at https://figshare.com/projects/Single-Cell_ChIP-seq_of_Mouse_Stromal_Cells_in_PDX_tumour_models_of_resistance/66419).<br><b>scATAC-seq datasets:</b> The single-cell ATAC-seq dataset is composed of two cell types derived from two acute myeloid leukaemia (AML) patient (blastocytes (blast) and leukemic stem cells (LSC) produced in (Corces et al., 2016)) as well as multiple cell lines : GM12878, TF1, BJ, H1, HL60, K562 (3 replicates) produced in (Buenrostro et al., 2015), K562 (3 replicates) produced in (Schep et al., 2017); monocytes (Mono) and lymphoid primed multipotent progenitor (LMPP) produced in (Corces et al., 2016)). The count matrix of reads in peaks was downloaded from GEO accession number GSE99172, split into distinct matrices for each sample and formatted to be accepted as input by ChromSCape. Code availability Source code, guidelines for installation and use of the application are provided at https://github.com/vallotlab/ChromSCape. A Docker environment containing all libraries required to launch the application is also available on DockerHub at https://hub.docker.com/repository/docker/pacomito/chromscape, with all set-up steps clearly described on the GitHub repository.

本文件夹包含一套单细胞染色质免疫沉淀测序（scChIP-seq）与一套单细胞转座酶可及性测序（scATAC-seq）数据集的三份分析成果，用于通过ChromSCape工具（https://github.com/vallotlab/ChromSCape）进行可视化展示。<b><br></b><b>数据集</b><br><b><br></b><b>H3K27me3 单细胞染色质免疫沉淀测序数据集：</b>本数据集的样本为来自两名不同人类供体的患者来源异种移植（PDX）模型中的小鼠细胞（Grosselin等人，2019）。原始FASTQ测序读段通过本团队最新版的scChIP-seq数据处理流程进行质控与分析，该流程可更精准地去除PCR与反转录重复序列（代码开源地址：https://github.com/vallotlab/scChIPseq_DataEngineering），最终生成50kbp分箱计数矩阵作为ChromSCape的输入文件（计数矩阵开源地址：https://figshare.com/projects/Single-Cell_ChIP-seq_of_Mouse_Stromal_Cells_in_PDX_tumour_models_of_resistance/66419）。<br><b>scATAC-seq 数据集：</b>本单细胞ATAC-seq数据集包含两类源自两名急性髓系白血病（AML）患者的细胞类型（即原始血细胞（blast）与白血病干细胞（LSC），数据来自Corces等人2016年的研究），同时涵盖多株细胞系：来自Buenrostro等人2015年研究的GM12878、TF1、BJ、H1、HL60、K562细胞系（3次生物学重复）；来自Schep等人2017年研究的K562细胞系（3次生物学重复）；以及来自Corces等人2016年研究的单核细胞（Mono）与淋巴系定向多能祖细胞（LMPP）。本数据集的峰区读段计数矩阵从GEO数据库登录号GSE99172下载，随后按样本拆分为独立矩阵并完成格式转换，以适配ChromSCape的输入要求。<br><b>代码开源说明</b>：本应用的源代码、安装与使用指南已开源至https://github.com/vallotlab/ChromSCape。此外，DockerHub平台（https://hub.docker.com/repository/docker/pacomito/chromscape）提供了包含所有运行依赖库的Docker镜像，GitHub仓库中已详细描述了所有配置步骤。