我想知道是否可以在FeatureScatter函数中为每个集群绘制facet_grid图。我想要绘制的两个特性是由feature1和feature2定义的,方面应该是我的对象中定义为pbmc.big$seurat_clusters中的级别的集群。
FeatureScatter(object = pbmc.big,
feature1 = "MALAT1",
feature2 = "percent.mito",
plot.cor = T)发布于 2021-03-13 17:42:58
值得一提的是,您使用的数据可以从this link下载并像这样创建:
library(Seurat)
library(magrittr)
pbmc.big <- Read10X(data.dir = "../data/pbmc3k/filtered_gene_bc_matrices/hg19/")
pbmc.big <- CreateSeuratObject(counts = pbmc.big)
pbmc.big$percent.mito = PercentageFeatureSet(pbmc.big,pattern="^MT-")运行群集:
pbmc.big = pbmc.big %>%
SCTransform() %>%
RunPCA() %>%
RunTSNE(dims=1:15) %>%
FindNeighbors(dims=1:15) %>%
FindClusters(res=0.1)你可以像这样刻面:
g = FeatureScatter(object = pbmc.big,
feature1 = "MALAT1",
feature2 = "percent.mito",
plot.cor = TRUE)
g + facet_wrap(~colors)

缺少相关性,如果需要的话,一种方法是提取变量并绘制图表:
library(ggpubr)
data.frame(cluster = Idents(pbmc.big),
MALAT1 = FetchData(pbmc.big,"MALAT1"),
percent.mito = FetchData(pbmc.big,"percent.mito")) %>%
ggplot(aes(x=MALAT1 , y= percent.mito, col = cluster)) +
geom_point(size=1) +
facet_wrap(~cluster)+
stat_cor(method = "pearson")

https://stackoverflow.com/questions/66135601
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