ComplexHeatmap相关性分析绘制热图

加载包、数据

使用Hmisc包rcorr()函数计算一个矩阵的所有可能的列的皮尔逊或斯皮尔曼相关系数,对于大量的基因数据,该方法非常快。ComplexHeatmap制作热图。

#载入包
BiocManager::install("ComplexHeatmap")
install.packages("Hmisc")
library(Hmisc)
library(ComplexHeatmap)
#载入数据
corMatrix[1:4,1:4]
                 ENSG00000082929 ENSG00000083622 ENSG00000093100 ENSG00000099869
TCGA-08-0386-01A       2.3550539               0      0.00000000       1.1377001
TCGA-14-1034-01A       0.6145029               0      0.03393831       0.0000000
TCGA-27-2524-01A       1.6513328               0      0.00000000       0.1950819
TCGA-19-4065-01A       3.0244148               0      0.03645590       0.9603883

相关性分析

#相关性分析
correlation = rcorr(corMatrix)
#基因太多,rows,cols用于选取部分基因作图
head(cols)
[1] "ENSG00000257703" "ENSG00000277930" "ENSG00000223442" 
     "ENSG00000236711" "ENSG00000236778" "ENSG00000251556"
data_P = data.frame(ifelse(correlation$P[rows,cols] < 0.0001, "***", ""))
data_r = correlation$r[rows,cols]

ComplexHeatmap绘制热图

ComplexHeatmap画相关性热图,设置参数cell_fun ,使热图方格中显示文字,显示内容,位置等依据data_p矩阵调整。

data_r[1:4,1:4]
                ENSG00000257703 ENSG00000277930 ENSG00000223442 ENSG00000236711
ENSG00000163568      0.09428102       0.1984986      0.21882686     0.137267053
ENSG00000137752     -0.29532155      -0.2723464     -0.16631483    -0.259307443
ENSG00000164305     -0.02606845      -0.3542482      0.01840446     0.005245428
ENSG00000196954     -0.46733087      -0.2751825     -0.19537846    -0.312062708

heatmap_legend_param = list(title = "P < 0.0001\n ***\n \nCorrelations ",title_position = "topcenter",legend_direction="vertical",
                            legend_direction = "horizontal",grid_width = unit(15, "mm"),grid_height = unit(8, "mm"))

Heatmap(data_r, cluster_rows =FALSE,cluster_columns = FALSE,col = rev(redblue(100)),
        cell_fun = function(j, i, x, y, width, height, fill) {
          grid.text(data_P[i,j], x = x, y = y,gp = gpar(fontsize = 10,col="black"))},
        column_names_rot = 45,row_names_side = "left",heatmap_legend_param=heatmap_legend_param
        )

颜色代表相关性大小,***表示p值小于0.0001.


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