已有基因表达矩阵(log2CPM)txt文件和样本分组文件,画3DPCA的R语言代
时间: 2024-01-23 15:04:18 浏览: 67
基于Gabor和2DPCA的单次训练样本人脸识别
好的,下面是R语言代码,你可以根据你的数据文件路径进行修改:
```R
# 导入必要的包
library(plotly)
library(dplyr)
# 导入基因表达矩阵和样本分组信息
expr_matrix <- read.table("path/to/expr_matrix.txt", header = TRUE, row.names = 1)
sample_info <- read.table("path/to/sample_info.txt", header = TRUE)
# 对基因表达矩阵进行log2转换
expr_matrix_log2 <- log2(expr_matrix + 1)
# 对样本进行分组
groups <- sample_info$group
# 计算3DPCA主成分
pc <- prcomp(expr_matrix_log2, center = TRUE, scale. = TRUE)
pc_scores <- data.frame(pc$x[,1:3])
pc_scores$group <- groups
# 画3DPCA图
pca_plot <- plot_ly(data = pc_scores, x = ~PC1, y = ~PC2, z = ~PC3, color = ~group, type = "scatter3d", mode = "markers")
pca_plot <- pca_plot %>% add_markers(showlegend = TRUE, marker = list(size = 2, opacity = 0.8))
pca_plot <- pca_plot %>% layout(scene = list(xaxis = list(title = "PC1"), yaxis = list(title = "PC2"), zaxis = list(title = "PC3")))
pca_plot
```
这段代码会将3DPCA图绘制在RStudio中,如果你想要在网页中查看图像,可以将`pca_plot`对象保存为html文件,通过浏览器打开即可。
阅读全文