绘制二进制值和连续值的热图

Question

我有一个路径分析矩阵。如果不是0，每条通路中的基因都会得到1。我也有基因的折叠变化。我试着画出这一点，但将变化与基因的缺失和伪装混淆了，比如：

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我试过了

heatmap(m)

dput(m)
structure(c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 
1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 
0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 
1, 1, 1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 
1, 1, 1, 1, -0.903826171835163, -0.247705285294349, -0.401239527828149, 
-1.20189443333319, -0.758305343685411, -1.10106389326754, -0.585488441571586, 
-0.610209849183418, -1.28841166063443, -1.2443689942311, -0.44380661806954, 
-0.393767679922636, -0.9865911233588, -1.16638985537113, -0.846196153682942, 
-1.08069734237831, -0.585488441571586, -0.501442757103725, -1.09515274600357, 
-1.28841166063443, -0.758305343685411, -0.358909656766957, -0.435604213681894, 
-0.233037798755743, -0.401239527828149, -1.28841166063443, -0.563163557390339, 
-1.08069734237831, -0.247705285294349, -0.903826171835163, -0.9865911233588, 
0.377359646511066, 0.453386357728066, 1.70862112102298, 0.532342427101257, 
1.61935728655752, 1.15211775940032, 0.265720938549918, 0.420856476956162, 
0.377359646511066, 0.350765937539292, 0.276646264257092), .Dim = c(42L, 
8L), .Dimnames = list(c("CCL2", "CCL4", "CD40", "CLCF1", "CSF3", 
"CXCL5", "CXCL6", "CXCL8", "IL1B", "IL6", "IL6R", "LTB", "OSM", 
"TNFRSF1B", "TNFSF10", "FOS", "FOSL1", "MMP3", "PTGS2", "TNFAIP3", 
"BCL2A1", "BIRC3", "CFLAR", "DDX58", "GADD45B", "TIRAP", "EDN1", 
"SOCS3", "IGF2", "JAK1", "NR4A1", "CACNA1D", "CALML5", "CALML6", 
"CCNA2", "CCND2", "CDK6", "MAPK1", "RBL1", "CDC6", "CDKN2C", 
"SMC3"), c("Cytokine-cytokine receptor interaction", "IL-17 signaling", 
"NF-kappa B signaling", "TNF signaling", "PI3K-Akt signaling", 
"Cellular senescence", "Cell cycle", "Log2FC")))

> head(m)
      Cytokine-cytokine receptor interaction IL-17 signaling
CCL2                                       1               1
CCL4                                       1               0
CD40                                       1               0
CLCF1                                      1               0
CSF3                                       1               1
CXCL5                                      1               1
      NF-kappa B signaling TNF signaling PI3K-Akt signaling
CCL2                     0             1                  0
CCL4                     1             0                  0
CD40                     1             0                  0
CLCF1                    0             0                  0
CSF3                     0             0                  1
CXCL5                    0             1                  0
      Cellular senescence Cell cycle     Log2FC
CCL2                    0          0 -0.9038262
CCL4                    0          0 -0.2477053
CD40                    0          0 -0.4012395
CLCF1                   0          0 -1.2018944
CSF3                    0          0 -0.7583053
CXCL5                   0          0 -1.1010639
> 

你能帮我解决这个问题吗？

Answer 1

热图(as.matrix(m，1:7))应该可以做到这一点。

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