• seurat单细胞数据分析实现 DimHeatmap函数


    上游分析:https://www.jianshu.com/p/4f7aeae81ef1

    001、

    cell <- pbmc[["pca"]]@cell.embeddings
    cell <- cell[order(cell[,1], decreasing = T),]
    cell <- rownames(cell)[c(1:10, (length(rownames(cell)) - 9):length(rownames(cell)))]
    cell                                                        ## 提取细胞
    
    feature <- pbmc[["pca"]]@feature.loadings
    feature <- feature[order(feature[,1], decreasing = T),]
    feature <- rownames(feature)[c(1:15, (length(rownames(feature)) - 14):length(rownames(feature)))]
    feature                                                     ## 提取基因
    
    dat <- pbmc[["RNA"]]@scale.data
    dat <- t(dat)[cell, feature]                                ## 提取绘图数据
    
    par(mar = c(1, 1, 3, 5))
    plot.new()
    image(dat, axes = FALSE,add = TRUE,                         ## 绘图
      col = PurpleAndYellow()
    )
    axis(side = 4, at = seq(0, 1, length = ncol(dat)), labels = colnames(dat),
      las = 1, tick = FALSE, mgp = c(0, -0.5, 0), cex.axis = 0.75
    )
    title(main = "PC1")

    002、标准答案

    DimHeatmap(pbmc, dims = 1, cells = 20, balanced = TRUE)

    003、使用默认颜色

    par(mar = c(1, 1, 3, 5))
    plot.new()
    image(dat, axes = FALSE,add = TRUE,
      #col = PurpleAndYellow()
    )
    axis(side = 4, at = seq(0, 1, length = ncol(dat)), labels = colnames(dat),
      las = 1, tick = FALSE, mgp = c(0, -0.5, 0), cex.axis = 0.75
    )
    title(main = "PC1")

    004、增加细胞名称

    par(mar = c(9, 1, 3, 5))
    plot.new()
    image(dat, axes = FALSE,add = TRUE,
      #col = PurpleAndYellow()
    )
    axis(side = 4, at = seq(0, 1, length = ncol(dat)), labels = colnames(dat),
      las = 1, tick = FALSE, mgp = c(0, -0.5, 0), cex.axis = 0.75
    )
    axis(side = 1, at = seq(0, 1, length = nrow(dat)), labels = rownames(dat),               ## 增加细胞名称
         las = 2, tick = FALSE, mgp = c(0, -0.5, 0), cex.axis = 0.75
    )
    title(main = "PC1")

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  • 原文地址:https://www.cnblogs.com/liujiaxin2018/p/16639053.html
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