pca分析下标出界不会

PCA分析：Error in pcaPredict[, 1:3] : 下标出界

if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("limma")

install.packages("scatterplot3d")

引用包
library(limma)
library(scatterplot3d)
setwd("C:\Users\hwk\Desktop\新建文件夹") 设置工作目录

#定义PCA分析函数
myPCA=function(input=null,output=null){
#读取表达数据文件
rt=read.table(input, header=T, sep="\t", check.names=F)
rt=as.matrix(rt)
rownames(rt)=rt[,1]
exp=rt[,2:ncol(rt)]
dimnames=list(rownames(exp),colnames(exp))
data=matrix(as.numeric(as.matrix(exp)),nrow=nrow(exp),dimnames=dimnames)
data=avereps(data)
data=data[rowMeans(data)>0.5,]

删除正常样品
type=sapply(strsplit(colnames(data),"\\-"),"[",4)
type=sapply(strsplit(type,""),"[",1)
type=gsub("2","1",type)
data=t(data[,type==0])
rownames(data)=gsub("(.*?)\\-(.*?)\\-(.*?)\\-(.*?)\\-.*","\\1\\-\\2\\-\\3",rownames(data))
    
读取risk风险文件
risk=read.table("risk.all.txt", header=T, sep="\t", row.names=1, check.names=F)
sameSample=intersect(rownames(data),rownames(risk))
data=data[sameSample,]
risk=risk[sameSample,]
group=as.vector(risk[,"risk"])
    
PCA分析
data.class <- rownames(data)
data.pca <- prcomp(data, scale. = TRUE)

绘制PCA图形
color=ifelse(group=="low",4,2)
pcaPredict=predict(data.pca)
pdf(file=output, width=7, height=7)
par(oma=c(1,1,2.5,1))
s3d=scatterplot3d(pcaPredict[,1:3], pch = 16, color=color, angle=35)
legend("top", legend = c("Low risk","High risk"),pch = 16, inset = -0.2, box.col="white", xpd = TRUE, horiz = TRUE,col=c(4,2))
dev.off()
}

绘制所有基因的PCA图，将04节课symbol.txt复制到当前目录
myPCA(input="symbol.txt",output="PCA.allGene.pdf")
绘制相关基因的PCA图，将09节课cuproptosisExp.txt复制到当前目录
myPCA(input="cuproptosisExp.txt",output="PCA.cuproptosisGene.pdf")
绘制相关lncRNA的PCA图，将09节课cuproptosisLncExp.txt复制到当前目录
myPCA(input="cuproptosisLncExp.txt",output="PCA.cuproptosisLncRNA.pdf")

读取风险文件,绘制模型lncRNA的PCA图，将14节课risk.all.txt复制到当前目录
risk=read.table("risk.all.txt", header=T, sep="\t", check.names=F, row.names=1)
data=risk[,3:(ncol(risk)-2)]
group=as.vector(risk[,"risk"])

PCA分析
data.class <- rownames(data)
data.pca <- prcomp(data, scale. = TRUE)

可视化
color=ifelse(group=="low",4,2)
pcaPredict=predict(data.pca)
pdf(file="PCA.riskLnc.pdf", width=6.5, height=6)
par(oma=c(1,1,2.5,1))
s3d=scatterplot3d(pcaPredict[,1:3], pch = 16, color=color, angle=35)
legend("top", legend = c("Low risk","High risk"),pch = 16, inset = -0.2, box.col="white", xpd = TRUE, horiz = TRUE,col=c(4,2))
dev.off()

img


一共372个样品

PCA分析
data.class <- rownames(data)
data.pca <- prcomp(data, scale. = TRUE)

可视化
color=ifelse(group=="low",4,2)
pcaPredict=predict(data.pca)
pdf(file="PCA.riskLnc.pdf", width=6.5, height=6)
par(oma=c(4,4,10,4))
s3d=scatterplot3d(pcaPredict[,1:3], pch = 16, color=color, angle=35)
Error in pcaPredict[, 1:3] : 下标出界
legend("top", legend = c("Low risk","High risk"),pch = 16, inset = -0.2, box.col="white", xpd = TRUE, horiz = TRUE,col=c(4,2))
Error in (function (s, units = "user", cex = NULL, font = NULL, vfont = NULL, :
plot.new has not been called yet
dev.off()
null device
1

我试过调绘图的大小不行，看了下应该是pcaPredict=predict(data.pca)出问题了，但不知道怎么改

不再出界，输出图像

遇到null值了