nichenet的原理大家可以参考文章10X单细胞(10X空间转录组)通讯分析之NicheNet,10X单细胞(10X空间转录组)空间相关性分析和cellphoneDB与NicheNet联合进行细胞通讯分析,单细胞分析之细胞交互-5:NicheNet多组间互作比较。 Differential NicheNet analysis between niches of interest 关于niche,在空间转录组上很常见,就是生态位、...
1.Browaeys R, Saelens W, Saeys Y. NicheNet: modeling intercellular communication by linking ligands to target genes[J]. Nature methods, 2020, 17(2): 159-162. 2.Zhang K, Erkan E P, Jamalzadeh S, et al. Longitudinal single-cel...
NicheNet(https://github.com/saeyslab/nichenetr)是一个计算不同细胞间相互作用的R包,通过细胞的表达数据与已知的信号和基因调控网络的相结合,预测相互作用细胞之间的配体-受体作用。通过将NicheNet应用于肿瘤和免疫细胞微环境数,可以推断出活性配体及其对相互作用细胞的基因调控作用。 NicheNet需要相互作用的细胞的人类...
#Perform the NicheNet analysis## 1. Define set of potential ligandsreceiver="Tcell"expressed_genes_receiver<- get_expressed_genes(receiver, sce, pct = 0.1) sender_celltypes<- c("Endo","Fib","Musc","Ker","APCs","Tcell","Mast","LY","Mela")list_expressed_genes_sender<- sender_cellty...
Although a standard NicheNet analysis takes less than 10 minutes to run, users often invest additional time in making decisions about the approach and parameters that best suit their biological question. This paper serves to aid in this decision-making process by describing the most appropriate ...
This training discusses how to analyze cell-cell communication from scRNA-seq data via the NicheNet analysis framework. The benefits and limitations of NicheNet are highlighted and compared to other approaches. The materials guide the course participant in applying NicheNet to their datasets. Most rec...
An open-source R implementation of NicheNet is available at GitHub (https://github.com/saeyslab/nichenetr). The release includes tutorials and example vignettes for the following analyses: ligand activity analysis on a gene set of interest, single-cell ligand activity analysis; ligand-to-target ...
Single-cell NicheNet’s ligand activity analysis:vignette("ligand_activity_single_cell", package="nichenetr") If you want to make a circos plot visualization of the NicheNet output, you can check following vignettes: Circos plot visualization to show active ligand-target links between interacting ce...
[1]"Perform DE analysis in receiver cell"## [1]"Perform NicheNet ligand activity analysis"## [1]"Infer active target genes of the prioritized ligands"## [1]"Infer receptors of the prioritized ligands"# 输出的是一个列表:nichenet_output%>%names()[1]"ligand_activities""top_ligands""top_...
Because we combined the expressed genes of each sender cell type, in this example, we will perform one NicheNet analysis by poolingallligands from all cell types together. Later on during the interpretation of the output,we will check which sender cell type expresses which ligand. ...