Merencanakan peta panas nilai biner dan kontinu

Saya memiliki matriks analisis jalur ini. Gen di setiap jalur mendapat 1 jika bukan 0. Saya juga mengalami perubahan lipat untuk gen. Saya mencoba memplot ini tetapi melipat perubahan menjadi bingung dengan ketidakhadiran dan kepura-puraan gen seperti:

masukkan deskripsi gambar di sini

saya telah mencoba

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
>

Bisakah Anda membantu mengatasi hal ini?


r heatmap
person user6517    schedule 12.02.2020    source sumber
comment
Tidak yakin apa yang Anda harapkan, tetapi tampaknya ini memplot apa yang Anda masukkan, dengan normalisasi baris (yaitu scale="row").   -  person user12728748    schedule 12.02.2020

Jawaban (1)


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heatmap(as.matrix(m[,1:7])) seharusnya berhasil. masukkan deskripsi gambar di sini

person shome    schedule 12.02.2020
comment
Namun maksudnya memiliki peta panas yang menunjukkan nilai biner dan kolom kontinu, bukan hanya mengabaikan kolom kontinu - person Angel; 12.02.2020