前面学习过单细胞marker基因常见的展示图一般有：点图，气泡图，小提琴图等。但是经常面临的问题是多个marker基因的同时展示，大多数paper使用的是气泡图，今天我们来测试怎么用小提琴图好好的展示。
测试数据，我们还是用pbmc4k和pbmc8k的测试数据。
先常规的合并，聚类降维等分析，因为只做测试，没去调参数的细节。
library(Seurat)
library(dittoSeq)
library(ggplot2)
library(harmony)
pbmc4k.data <- Read10X(data.dir = "pbmc4k/filtered_gene_bc_matrices/GRCh38/")
pbmc4k <- CreateSeuratObject(counts = pbmc4k.data, project = "PBMC4K")
pbmc4k
pbmc8k.data <- Read10X(data.dir = "pbmc8k/filtered_gene_bc_matrices/GRCh38/")
pbmc8k <- CreateSeuratObject(counts = pbmc8k.data, project = "PBMC8K")
pbmc8k
pbmc.combined <- merge(pbmc4k, y = pbmc8k, add.cell.ids = c("4K", "8K"), project = "PBMC12K")
pbmc.combined
head(colnames(pbmc.combined))
table(pbmc.combined$orig.ident)
all <- pbmc.combined
all<- NormalizeData(all, normalization.method ="LogNormalize", scale.factor =10000)
all <- FindVariableFeatures(all, selection.method ="vst", nfeatures =5000)
all.genes <- rownames(all)
all <- ScaleData(all, features = all.genes)
all <- RunPCA(all, features = VariableFeatures(object = all))
all <- RunHarmony(all, "orig.ident",assay.use="RNA")
all <- FindNeighbors(all, dims = 1:30,reduction = "harmony")
all <- FindClusters(all, resolution = 0.8)
all <- RunUMAP(all, dims = 1:30,reduction = "harmony")
all <- RunTSNE(all, dims = 1:30,reduction = "harmony")
#我们展示一些常见的marker基因。
makers <- c("MS4A1", "GNLY", "CD3E", "CD14", "FCER1A", "FCGR3A", "LYZ", "PPBP", "CD8A")
#下面是一个常规的堆叠小提琴图
VlnPlot(all,features = makers,stack=T,pt.size=0,flip = T,add.noise = T)+
theme(axis.text.y = element_blank(),
axis.ticks.y = element_blank(),
axis.title = element_blank(),
axis.text.x = element_text(colour = 'black',size = 10,angle = 90),
legend.position = 'none')
因为我们有2组不同的来源，还可以展示分组小提琴图。
VlnPlot(all, features = makers,stack=T,pt.size=0,split.by = 'orig.ident',flip = T,add.noise = T)+
theme(axis.text.y = element_blank(),
axis.ticks.y = element_blank(),
axis.title = element_blank(),
axis.text.x = element_text(colour = 'black',size = 10,angle = 90),
legend.position = 'top',
legend.title=element_blank(),
legend.box.background = element_blank(),
legend.text = element_text(color="black",size=10),
legend.spacing.x=unit(0.2,'cm'),
legend.key.width=unit(0.4,'cm'),
legend.key.height=unit(0.4,'cm'),
legend.background=element_blank())
#还可以用split参数进行分半小提琴图展示：
VlnPlot(all, features = makers,stack=T,pt.size=0,flip = T,add.noise = T,split.by = 'orig.ident',split.plot = T)+
theme(axis.text.y = element_blank(),
axis.ticks.y = element_blank(),
axis.title = element_blank(),
axis.text.x = element_text(colour = 'black',size = 10,angle = 90),
legend.position = 'none')
#也可以进行改颜色，对其进行调整。
VlnPlot(all, features = makers,stack=T,pt.size=0,flip = T,add.noise = T,split.by = 'orig.ident',
cols = c("limegreen", "navy"),
split.plot = T)+
theme(axis.text.y = element_blank(),
axis.ticks.y = element_blank(),
axis.title = element_blank(),
axis.text.x = element_text(colour = 'black',size = 10,angle = 90),
legend.position = 'none')
