scMetabolism包用于评估单细胞代谢激活分数

DoubleHelix

发布于 2023-09-06 10:07:23

4071

发布于 2023-09-06 10:07:23

1.包的安装

install.packages(c("devtools", "data.table", "wesanderson", "Seurat", "devtools", "AUCell", "GSEABase", "GSVA", "ggplot2","rsvd"))
devtools::install_github("YosefLab/VISION@v2.1.0") #Please note that the version would be v2.1.
devtools::install_github("wu-yc/scMetabolism")

2.计算代谢激活分数

subcell_sce是已经注释过的Seurat对象。

load("sce.Rdata")
countexp.Seurat<-sc.metabolism.Seurat(obj = subcell_sce, 
                                      method = "AUCell", 
                                      imputation = F, ncores = 2, 
                                      metabolism.type = "KEGG")

method有4种：VISION, AUCell, ssgsea和gsva。作者推荐VISION。

MedBioInfoCloud: rownames(countexp.Seurat@assays[["METABOLISM"]][["score"]])[1:6]
[1] "Glycolysis / Gluconeogenesis"            
[2] "Citrate cycle (TCA cycle)"               
[3] "Pentose phosphate pathway"               
[4] "Pentose and glucuronate interconversions"
[5] "Fructose and mannose metabolism"         
[6] "Galactose metabolism"

3.可视化

DimPlot.metabolism(obj = countexp.Seurat, 
                   pathway = "Pentose phosphate pathway", 
                   dimention.reduction.type = "umap", 
                   dimention.reduction.run = F, size = 1)

DimPlot.metabolism(obj = countexp.Seurat, 
                   pathway = "Citrate cycle (TCA cycle)", 
                   dimention.reduction.type = "tsne", 
                   dimention.reduction.run = F, size = 1)

input.pathway<-rownames(countexp.Seurat@assays[["METABOLISM"]][["score"]])[1:6]
DotPlot.metabolism(obj = countexp.Seurat, pathway = input.pathway, 
                   phenotype = "seurat_clusters", norm = "y")