已有基因表达矩阵（log2CPM）txt文件和样本分组文件，使用scatterplot3d画3DPCA的R语言代

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：

# 导入必要的包
library(scatterplot3d)

# 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 <- scatterplot3d(pc_scores, color = groups, pch = 19, type = "h", angle = 45, grid = FALSE, box = FALSE, xlab = "PC1", ylab = "PC2", zlab = "PC3")
legend("topright", legend = unique(groups), pch = 19, col = unique(groups), cex = 0.8)

这段代码会将3DPCA图绘制在RStudio中，你可以通过鼠标拖动来旋转图像。如果你想要保存图片，可以将画图函数替换为`png()`或`pdf()`函数，然后在绘图结束后使用`dev.off()`命令关闭设备。例如：

png("path/to/pca.png", width = 800, height = 600)
scatterplot3d(pc_scores, color = groups, pch = 19, type = "h", angle = 45, grid = FALSE, box = FALSE, xlab = "PC1", ylab = "PC2", zlab = "PC3")
legend("topright", legend = unique(groups), pch = 19, col = unique(groups), cex = 0.8)
dev.off()