去除单细胞批次效应影响的软件有mnnCorrect,该软件利用不同批次中的细胞之间的相互最邻近邻居来确定事后批次之间的共同生物学现象,这种方法经过改进可以为Seurat的 canonical correlation analysis (CCA)找到“锚点”。mnnCorrect使用PCA从基因表达矩阵中删除了批处理效应,而CCA则是将细胞投射到一个公共的基因相关空间中并对...
Seurat采用Tirosh等人提出的方法,根据已知标记基因G1/S和G2/M的平均归一化表达值对细胞进行评分。 一旦细胞被分配了一种细胞周期阶段,两种工具都使用一般线性模型来回归差异。此外,Seurat提供了一个选项,仅回归掉G1/S和G2/M细胞之间的差异,同时保留细胞周期的细胞和非细胞周期的细胞之间的差异。如果有人对细胞周期...
Seurat:https://satijalab.org/seurat/get_started.html; Scanpy:Tutorials - Scanpy 1.6.2.dev0+g099be48b.d20210114 documentation). 基于以上问题,作者综述了目前scRNA-seq分析流程、步骤和方法(Figure 1),提出了一套目前最佳的实践分析流程,详见theislab/single-cell-tutorial. 这套分析流程在Jupyter–Ipython...
常用的归一化Normalize处理目的是将离散程度很大的数据集中化,对数据转换能够让同一基因在不同样本具有可比性(RPKM/TPM),在Seurat中LogNormalize便是利用log1p(value/colSums[cell-idx] *scale_factor) 常用的标准化Scale是基于之前归一化结果,再添加z-score计算,考虑到了不同样本对表达量的影响,消除了表达的平均水平...
Detailed workflow tutorial 35:53 9 The Beginner's guide to bulk RNA sequencing vs single-cell RNA Sequencing 12:24 10 Single-cell Trajectory analysis using Monocle3 and Seurat _ Step-by-step tuto 48:43 11 Automatic cell-annotation for single-cell RNA-Seq data using a reference data 34:12...
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,......
Single-cell technologies, particularly single-cell RNA sequencing (scRNA-seq) methods, together with associated computational tools and the growing availability of public data resources, are transforming drug discovery and development. New opportunities are emerging in target identification owing to improved...
The count table, a numeric matrix of genes × cells, is the basic input data structure in the analysis of single-cell RNA-sequencing data. A common preprocessing step is to adjust the counts for variable sampling efficiency and to transform them so
Seurat, Seurat_SNN To test Seurat, we followed the guided clustering workflow recommended in the tutorial at [11] by first applying the recommended cell quality filtering based on the number of detected genes, minimum 200 per cell, and percentage of reads from mitochondrial genes. Then, as reco...
Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc. - seandavi/awesome-single-cell