#生成隨機顏色
> randomColor <- function() {
? paste0("#",paste0(sample(c(0:9, letters[1:6]), 6, replace = TRUE),collapse = ""))
}
# 生成100個隨機顏色
> randomColors <- replicate(100,randomColor())
> seurat=readRDS("seurat.rds")#讀取數據
#歸一化
> all.genes <- rownames(seurat)
> seurat <- ScaleData(seurat, features = all.genes)
# PCA降維
> seurat <- Seurat::RunPCA(seurat, features = VariableFeatures(object = seurat))
> seurat <- Seurat::RunTSNE(seurat,dims = 1:20)
> pdf(file = "降維tsne圖.pdf",width =7.5,height = 5.5)
> DimPlot(seurat, reduction = "tsne",pt.size = 0.5)+theme_classic()+theme(panel.border = element_rect(fill=NA,color="black", size=0.5, linetype="solid"),legend.position = "right") #top為圖列位置最上方，除此之外還有right、left、bottom(意思同英文)
> dev.off()
> pdf(file = "降維pca圖.pdf",width =7.5,height = 5.5)
> DimPlot(seurat, reduction = "pca",pt.size = 0.5)+theme_classic()+theme(panel.border = ?element_rect(fill=NA,color="black", size=0.5, linetype="solid"),legend.position = "right")
> dev.off()
> colaa=distinctColorPalette(100)
> pdf(file = "降維tsne單樣品分布圖.pdf",width =12,height = 10)
> coords <- as.data.frame(seurat@reductions$tsne@cell.embeddings[, c(1, 2)])
> names(coords) <- c("tSNE_1", "tSNE_2")
# 添加聚類信息
> coords$cluster <- seurat@meta.data$Type
# 繪制 t-SNE 圖
> ggplot(coords, aes(x = tSNE_1, y = tSNE_2, color = cluster)) +
? geom_point(size = 0.5) +
? ggtitle("This is the plot title") +
? theme(legend.position = "bottom")
> dev.off()
#harmony 去批次
> seurat <- RunHarmony(seurat, group.by.vars = "Type")
## 鑒定高變基因（由于去除了存在批次的細胞，高變基因可能會發生改變，因此需要重新鑒定高變基因）
> seurat <- FindVariableFeatures(seurat, selection.method = "vst", nfeatures = 2000)
# 提取前10的高變基因
> top10 <- head(VariableFeatures(seurat), 10)
# 展示高變基因
> plot1 <- VariableFeaturePlot(seurat)
> plot1
> plot2 <- LabelPoints(plot = plot1, points = top10, repel = TRUE)
> pdf(file = "去批次后鑒定高變基因.pdf",width =7,height = 6)
> plot2 ? ? ? ? ? ? ? ? ?
> dev.off()
#降維可視化
> pdf(file = "harmony去批次pca圖.pdf",width =7.5,height = 5.5)
> DimPlot(seurat, reduction = "harmony",pt.size = 0.5)+theme_classic()+theme(panel.border = element_rect(fill=NA,color="black", size=0.5, linetype="solid"),legend.position = "right")
> dev.off()
> seurat <- Seurat::RunTSNE(seurat,dims = 1:20,reduction ='harmony')
> pdf(file = "去批次后tsne圖.pdf",width =7.5,height = 5.5)
> DimPlot(seurat, reduction = "tsne",pt.size = 0.5)+theme_classic()+theme(panel.border = element_rect(fill=NA,color="black", size=0.5, linetype="solid"),legend.position = "right")
> dev.off()
> pdf(file = "去批次后tsne單樣本分布圖.pdf",width =12,height = 7.5)
# 添加聚類信息
> coords$cluster <- seurat@meta.data$Type
# 繪制 t-SNE 圖
> ggplot(coords, aes(x = tSNE_1, y = tSNE_2, color = cluster)) +
? geom_point(size = 0.5) +
? ggtitle("This is the plot title") +
? theme(legend.position = "bottom")
> dev.off()
#繪制去批次后tsne單樣本分布圖
> ggplot(coords, aes(x = tSNE_1, y = tSNE_2, color = cluster)) +
? geom_point(size = 0.5) +
? ggtitle("This is the plot title") +
? theme(legend.position = "bottom")
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