R 中基因强度值的热图
Heatmap of Gene intensity values in R
我有这样的数据:
Gene
HBEC-KT-01
HBEC-KT-02
HBEC-KT-03
HBEC-KT-04
HBEC-KT-05
Primarycells-02
Primarycells-03
Primarycells-04
Primarycells-05
BPIFB1
15726000000
15294000000
15294000000
14741000000
22427000000
87308000000
2.00E+11
1.04E+11
1.51E+11
LCN2
18040000000
26444000000
28869000000
30337000000
10966000000
62388000000
54007000000
56797000000
38414000000
C3
2.52E+11
2.26E+11
1.80E+11
1.80E+11
1.78E+11
46480000000
1.16E+11
69398000000
78766000000
MUC5AC
15647000
8353200
12617000
12221000
29908000
40893000000
79830000000
28130000000
69147000000
MUC5B
965190000
693910000
779970000
716110000
1479700000
38979000000
90175000000
41764000000
50535000000
ANXA2
14705000000
18721000000
21592000000
18904000000
22657000000
28163000000
24282000000
21708000000
16528000000
我想使用 R 制作如下所示的热图。我正在关注一篇论文,他们引用了“热图是使用‘pheatmap’包76生成的,其中应用了相关聚类距离行”。这是他们的热图。
我想要这样的东西,我正在尝试按照教程使用 R 制作一个,但我是 R 语言的新手,对 R 一无所知。
这是我的代码。
df <- read.delim("R.txt", header=T, row.names="Gene")
df_matrix <- data.matrix(df)
pheatmap(df_matrix,
main = "Heatmap of Extracellular Genes",
color = colorRampPalette(rev(brewer.pal(n = 10, name = "RdYlBu")))(10),
cluster_cols = FALSE,
show_rownames = F,
fontsize_col = 10,
cellwidth = 40,
)
这就是我得到的。
当我尝试使用集群时,出现错误。
pheatmap(
mat = df_matrix,
scale = "row",
cluster_column = F,
show_rownames = TRUE,
drop_levels = TRUE,
fontsize = 5,
clustering_method = "complete",
main = "Hierachical Cluster Analysis"
)
Error in hclust(d, method = method) :
NA/NaN/Inf in foreign function call (arg 10)
有人可以帮我写代码吗?
您可以使用 scale
对数据进行归一化,以获得更均匀的着色。此处,每个样本的平均表达式设置为 0。表达低于平均值的基因具有负 z 分数:
library(tidyverse)
library(pheatmap)
data <- tribble(
~Gene, ~`HBEC-KT-01`, ~`HBEC-KT-02`, ~`HBEC-KT-03`, ~`HBEC-KT-04`, ~`HBEC-KT-05`, ~`Primarycells-03`, ~`Primarycells-04`, ~`Primarycells-05`,
"BPIFB1", 1.5726e+10, 1.5294e+10, 1.5294e+10, 1.4741e+10, 2.2427e+10, 2e+11, 1.04e+11, 1.51e+11,
"LCN2", 1.804e+10, 2.6444e+10, 2.8869e+10, 3.0337e+10, 1.0966e+10, 5.4007e+10, 5.6797e+10, 3.8414e+10,
"C3", 2.52e+11, 2.26e+11, 1.8e+11, 1.8e+11, 1.78e+11, 1.16e+11, 6.9398e+10, 7.8766e+10,
"MUC5AC", 15647000, 8353200, 12617000, 12221000, 29908000, 7.983e+10, 2.813e+10, 6.9147e+10,
"MUC5B", 965190000, 693910000, 779970000, 716110000, 1479700000, 9.0175e+10, 4.1764e+10, 5.0535e+10,
"ANXA2", 1.4705e+10, 1.8721e+10, 2.1592e+10, 1.8904e+10, 2.2657e+10, 2.4282e+10, 2.1708e+10, 1.6528e+10
)
data %>%
mutate(across(where(is.numeric), scale)) %>%
column_to_rownames("Gene") %>%
pheatmap(
scale = "row",
cluster_column = F,
show_rownames = FALSE,
show_colnames = TRUE,
treeheight_col = 0,
drop_levels = TRUE,
fontsize = 5,
clustering_method = "complete",
main = "Hierachical Cluster Analysis (z-score)",
)
由 reprex package (v2.0.1)
于 2021-09-26 创建
我有这样的数据:
Gene | HBEC-KT-01 | HBEC-KT-02 | HBEC-KT-03 | HBEC-KT-04 | HBEC-KT-05 | Primarycells-02 | Primarycells-03 | Primarycells-04 | Primarycells-05 |
---|---|---|---|---|---|---|---|---|---|
BPIFB1 | 15726000000 | 15294000000 | 15294000000 | 14741000000 | 22427000000 | 87308000000 | 2.00E+11 | 1.04E+11 | 1.51E+11 |
LCN2 | 18040000000 | 26444000000 | 28869000000 | 30337000000 | 10966000000 | 62388000000 | 54007000000 | 56797000000 | 38414000000 |
C3 | 2.52E+11 | 2.26E+11 | 1.80E+11 | 1.80E+11 | 1.78E+11 | 46480000000 | 1.16E+11 | 69398000000 | 78766000000 |
MUC5AC | 15647000 | 8353200 | 12617000 | 12221000 | 29908000 | 40893000000 | 79830000000 | 28130000000 | 69147000000 |
MUC5B | 965190000 | 693910000 | 779970000 | 716110000 | 1479700000 | 38979000000 | 90175000000 | 41764000000 | 50535000000 |
ANXA2 | 14705000000 | 18721000000 | 21592000000 | 18904000000 | 22657000000 | 28163000000 | 24282000000 | 21708000000 | 16528000000 |
我想使用 R 制作如下所示的热图。我正在关注一篇论文,他们引用了“热图是使用‘pheatmap’包76生成的,其中应用了相关聚类距离行”。这是他们的热图。
我想要这样的东西,我正在尝试按照教程使用 R 制作一个,但我是 R 语言的新手,对 R 一无所知。
这是我的代码。
df <- read.delim("R.txt", header=T, row.names="Gene")
df_matrix <- data.matrix(df)
pheatmap(df_matrix,
main = "Heatmap of Extracellular Genes",
color = colorRampPalette(rev(brewer.pal(n = 10, name = "RdYlBu")))(10),
cluster_cols = FALSE,
show_rownames = F,
fontsize_col = 10,
cellwidth = 40,
)
这就是我得到的。
当我尝试使用集群时,出现错误。
pheatmap(
mat = df_matrix,
scale = "row",
cluster_column = F,
show_rownames = TRUE,
drop_levels = TRUE,
fontsize = 5,
clustering_method = "complete",
main = "Hierachical Cluster Analysis"
)
Error in hclust(d, method = method) :
NA/NaN/Inf in foreign function call (arg 10)
有人可以帮我写代码吗?
您可以使用 scale
对数据进行归一化,以获得更均匀的着色。此处,每个样本的平均表达式设置为 0。表达低于平均值的基因具有负 z 分数:
library(tidyverse)
library(pheatmap)
data <- tribble(
~Gene, ~`HBEC-KT-01`, ~`HBEC-KT-02`, ~`HBEC-KT-03`, ~`HBEC-KT-04`, ~`HBEC-KT-05`, ~`Primarycells-03`, ~`Primarycells-04`, ~`Primarycells-05`,
"BPIFB1", 1.5726e+10, 1.5294e+10, 1.5294e+10, 1.4741e+10, 2.2427e+10, 2e+11, 1.04e+11, 1.51e+11,
"LCN2", 1.804e+10, 2.6444e+10, 2.8869e+10, 3.0337e+10, 1.0966e+10, 5.4007e+10, 5.6797e+10, 3.8414e+10,
"C3", 2.52e+11, 2.26e+11, 1.8e+11, 1.8e+11, 1.78e+11, 1.16e+11, 6.9398e+10, 7.8766e+10,
"MUC5AC", 15647000, 8353200, 12617000, 12221000, 29908000, 7.983e+10, 2.813e+10, 6.9147e+10,
"MUC5B", 965190000, 693910000, 779970000, 716110000, 1479700000, 9.0175e+10, 4.1764e+10, 5.0535e+10,
"ANXA2", 1.4705e+10, 1.8721e+10, 2.1592e+10, 1.8904e+10, 2.2657e+10, 2.4282e+10, 2.1708e+10, 1.6528e+10
)
data %>%
mutate(across(where(is.numeric), scale)) %>%
column_to_rownames("Gene") %>%
pheatmap(
scale = "row",
cluster_column = F,
show_rownames = FALSE,
show_colnames = TRUE,
treeheight_col = 0,
drop_levels = TRUE,
fontsize = 5,
clustering_method = "complete",
main = "Hierachical Cluster Analysis (z-score)",
)
由 reprex package (v2.0.1)
于 2021-09-26 创建