We benchmark the proposed methods with known DEG analysis tools using two real public datasets. The results show that the two procedures can be very competitive with existing methods (scVI, SCDE, MAST, and DEseq
利用Human ESC scRNA-seq dataset for differential expression analysis 二次采样出三个较小的子集,绘制了数据的分布以及插补值之后的表达值均值 (mean) 与标准偏差 (SD) (参见下图6)。所有这些结果表明,scIGANs对于由很少的基因 (约占检测到的基因的5%) 组成的小型数据集具有很强的表达力或细胞间差异,对于其他...
差异表达分析(Differential expression analysis) 细胞很多,每个细胞的基因也有很多,那么那些基因才是有意义的呢?需要一些统计手段来把这些基因识别出来,这就是差异表达分析,针对单细胞测序(特别是scRNA-seq)数据的特点,已经开发的算法和软件见下图: 差异分析常用工具 mark基因识别 通过差异分析来识别每个cluster下的标记基...
Human ESC scRNA-seq dataset for differential expression analysis包括批量RNA测序数据以及与之相匹配的scRNA-seq数据。使用DESeq2识别H1和DEC细胞之间的批量RNA测序数据以及与之相匹配的scRNA-seq数据的差异性表达基因 (DEG)。原始的scRNA-seq数据的零表达率比批量RNA测序数据更高(分别为49.1%和14.8%),并且共享的DEG...
Aspects of single-cell RNA sequencing (scRNA-seq) data, such as its sparsity and high cell–cell variability, have made it hard to apply statistical approaches developed for bulk RNA-seq analyses, such as differential gene expression Kim et al. present Memento, a tool that uses methods-of-...
Differential expression (DE) analysis and gene set enrichment (GSE) analysis are commonly applied in single cell RNA sequencing (scRNA-seq) studies. Here, we develop an integrative and scalable computational method, iDEA, to perform joint DE and GSE analysis through a hierarchical Bayesian framework...
2021). ST-seq data from 8 wild-type mice were integrated by canonical correlation analysis (CCA) and 6 clusters were obtained by unsupervised clustering. Following examination of each cluster by differential gene expression analysis (DGEA), scRNA-seq data were mapped back to ST-seq tissues using...
Single-cell Transcriptome Analysis Reveals Dynamic Cell Populations and Differential Gene Expression Patterns in Control and Aneurysmal Human Aortic Tissue 发表期刊:Circulation 影响因子:35.5 发表时间:2020.10 组学技术:scRNA-seq 胸升主动脉瘤(ATAA)是由主动脉壁逐渐减弱和扩张引起的,可导致主动脉夹层、破裂和其...
scRNA-seq differential expression analysis and cluster marker detection The R package MAST was used to perform all single-cell differential gene expression analyses and Likelihood ratio tests was performed to identify DEGs between two conditions. Benjamini–Hochberg multiple testing correction was used to...
Differential expression 差异表达(DE)对于scRNA-seq来说更具挑战性,因为不仅仅是比较每个基因的单一数值,而是可以比较表达水平的分布。另一个单细胞数据特有的挑战是,要比较的细胞组不是先验定义的。相反,通常是根据想要比较的表达水平来定义组。最近的一项比较得出结论,与特制方法相比,非参数Wilcoxon检验的表现非常好。