我们可以通过绘制伪时间坐标的直方图来找到这些亚稳态。 3.3 细胞水平的联合分析 - Cell-level analysis unification 聚类和轨迹推断代表单细胞数据的两个不同视角,并可以在粗粒度(coarse‐grained)的图形展示中进行统一。用点代表单细胞簇,轨迹作为簇之间相连的边,可以同时展示数据的静态和动态属性。这一联合分析在PAGA...
《Tutorial: guidelines for the computational analysis of single-cell RNA sequencing data》 Introduction 目前基于单细胞测序主要有两种建库技术,一种是主打细胞数量的10X platform,该技术的特点是提出了unique molecular identifiers(UMI),即每一个细胞对应唯一的barcode作为区分于其他细胞的标识符;简而言之就是测到的...
[1] Svensson V, Vento-Tormo R, Teichmann S A. Exponential scaling of single-cell RNA-seq in the past decade[J]. Nature Protocols, 2018, 13(4):599-604. [2] Malte D L., Fabian J T.. Current best practices in single‐cell RNA‐seq analysis: a tutorial. Molecular Systems Biology. ...
2.1.Expression Matrix - Bioinformatics Tutorial (http://ncrnalab.org)RSeQC判断链特异性（strand-spe...
2 共表达流程 Tutorial Preparing RNA-seq data for network construction Building a co-expression network Detecting co-expression modules Annotating a co-expression network Visualizing network 正文开始 1.1 Types of biological networks 生物网络可以包含不同的数据类型,用点(node)和边(edge)区分。常见的网络类型...
Single-cell RNA sequencing (scRNA-seq) is a popular and powerful technology that allows you to profile the whole transcriptome of a large number of individual cells. However, the analysis of the large volumes of data generated from these experiments requ
Data analysis tutorialExperimental workflowMonocleScanpySeuratSingle-cell RNA-seqgf-icfThanks to innovative sample-preparation and sequencing technologies, gene expression in individual cells can now be measured for thousands of cells in a single experiment. Since its introduction,......
Tutorial: integrative computational analysis of bulk RNA-sequencing data to characterize tumor immunity using RIMALin Yang, Jin Wang, Jennifer Altreuter, Aashna Jhaveri, Cheryl J. Wong, Li Song, Jingxin Fu, Len Taing, Sudheshna Bodapati, Avinash Sahu, Collin Tokheim, Yi Zhang,...
在我们的Github上有结合了已建立的当前最佳实践流程的案例研究:https://github.com/theislab/single-cell-tutorial/。我们在实际的示例工作流程中应用了当前的最佳实践来分析公共数据集。该分析流程使用Jupyter notebook和rpy2整合了R和Python的工具。结合现有的文档,这已经可以被视作一个可接受的分析流程模板了。
关于质控的详细信息可以参考https://rtsf.natsci.msu.edu/genomics/tech-notes/fastqc-tutorial-and-faq/,对每部分都有基本介绍。主要使用的软件包括:FastQC(对 Illumina 读数执行质控分析的流行工具)和 NGSQC(可以适用于任何平台)。 通过测序质控软件可以了解样本测序质量情况,针对质控的结果考虑是否弃用样本,以及...