bulk RNA-seq，用R语言中的scatterplot3d包画3DPCA示例

好的，以下是使用R语言中的scatterplot3d包画bulk RNA-seq数据的3DPCA示例代码：

首先，加载所需的库：

library(DESeq2)
library(scatterplot3d)

接下来，读入bulk RNA-seq数据，进行基于DESeq2的数据标准化和差异表达分析：

countdata <- read.table("bulk_RNAseq_countdata.txt", header = T, row.names = 1)
coldata <- read.table("bulk_RNAseq_coldata.txt", header = T, row.names = 1)
dds <- DESeqDataSetFromMatrix(countData = countdata, colData = coldata, design = ~condition)
dds <- DESeq(dds)
res <- results(dds, contrast = c("condition", "sample1", "sample2"))

然后，将差异表达基因的表达矩阵进行PCA分析：

pcaData <- prcomp(t(assay(rld[res$padj < 0.05, ])))

最后，使用scatterplot3d包进行3DPCA绘图：

scatterplot3d(pcaData$x[,1], pcaData$x[,2], pcaData$x[,3], color = coldata$condition, pch = 19, type = "h", angle = 70, main = "Bulk RNA-seq 3DPCA", xlab = "PC1", ylab = "PC2", zlab = "PC3")
legend("topright", legend = c("sample1", "sample2"), col = c("red", "blue"), pch = 19)

这样就可以得到bulk RNA-seq数据的3DPCA图了。