4. Perform NicheNet ligand activity analysis:rank the potential ligands based on the presence of their target genes in the gene set of interest (compared to the background set of genes) ligand_activities = predict_ligand_activities(geneset = geneset_oi, background_expressed_genes = background_...
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、...
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. ligands=lr_ne...
# Good idea to check which genes will be left out of the ligand activity analysis (=when not present in the rownames of the ligand-target matrix). # If many genes are left out, this might point to some issue in the gene naming (eg gene aliases and old gene symbols, bad human-mouse...
#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...
Perform NicheNet analysis starting from a Seurat object:vignette("seurat_wrapper", package="nichenetr") Perform NicheNet analysis starting from a Seurat object: step-by-step analysis:vignette("seurat_steps", package="nichenetr") People interested in building own models or benchmark own models again...
This is described as well in the other vignette Perform NicheNet analysis starting from a Seurat object: step-by-step analysis:vignette("seurat_steps", package="nichenetr"). tumors_remove = c("HN10","HN","HN12", "HN13", "HN24", "HN7", "HN8","HN23") CAF_ids = sample_info %...
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 ...
#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...
[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_...