limma：
setwd("F:\\NEW ANALYST\\marix\\marix-picture")
library(limma)
rt<-read.csv("GSE19743marix.txt",head=T,sep='\t',row.names = "gene")
rt1=log2(rt)
class<-c(rep("burn",28),rep("normal",25))
View(class)
design<-model.matrix(~factor(class))
colnames(design)<-c("burn","normal")
fit<-lmFit(rt1,design)
fit2<-eBayes(fit)
allDiff=topTable(fit2,adjust='fdr',coef=2,number=200000)
write.table(allDiff,file="limmaTab.txt",sep ='\t',quote = F)

CIBERSORT：
setwd("F:\\NEW ANALYST\\immune\\analysisI")
> source('Cibersort.R')
> library(preprocessCore)
> library(e1071)
> result1 <- CIBERSORT('LM22.txt','DATA.txt', perm = 1000, QN = T)
write.table(result,file="CIBERSORT",sep ='\t',quote = F)

ggolot2：
BiocManager::install("ggplot")
library(ggplot2)
ggplot(df,aes(groups,value,fill = type)) + 
  geom_boxplot(outlier.shape = 21,color = "black") + 
  theme_bw() + 
  labs(x = "Cell Type", y = "Estimated Proportion") +
  theme(legend.position = "top") + 
  theme(axis.text.x = element_text(angle=80,vjust = 0.5))+
  scale_fill_manual(values = mypalette(22)[c(6,1)])+ 
  stat_compare_means(aes(group = Group,label = ..p.signif..),method = "kruskal.test")
ggplot(data=a, aes(x=Mixture,y=value,fill=groups))+
  geom_violin(width=0.5,position = position_dodge(0.9))+
  geom_boxplot(width=0.4,position = position_dodge(0.9))+
  labs(x = "Cell Type", y = "Estimated Proportion")+
  theme(legend.position = "top")+
  theme(axis.text.x = element_text(angle=80,vjust = 0.5))+
  scale_fill_manual(values=c("4","2"))+
  stat_compare_means(aes(group=groups,label =..p.signif..),method = "t.test")

Affy：
BiocManager::install("affy")
library(affy)
setwd("F:\\NEW ANALYST\\marix\\GSE77791\\ALL")
  burn<- read.table("burn.txt",header = T,sep = "\t")
  hc<- read.table("hc.txt",header = T,sep = "\t")
  GLP<- read.table("GLP570.txt",header = T,sep = "\t")
cg=intersect(rownames(burn),rownames(hc))
all<-cbind(burn,hc,deparse.level = 1)
all<-merge(all,GLP,by=intersect(names(all),names(GLP)))
all1<-all(rownames("Gene.Symbol"))
a<-hc[c("RORA","NFATC2","CAMK4"),]
immune<-exprs(immune_gene)
all<-cbind(immu,burn,hc,deparse.level = 1)
head(immune_gene)
rawdata <- ReadAffy()
length(rawdata)
eset.mas5<- mas5(rawdata)
eset.rma <- rma(rawdata)
boxplot(exprSet)
boxplot(rawdata)
exprSet <- exprs(eset.rma)
exprSet1 <- exprs(rawdata)
write.table(exprSet,"expr_rma_matrix.txt", quote = F,sep='\t')
write.table(exprSet, file = "expr_rma_matrix.txt", append = FALSE, quote = TRUE, sep = " ",
            eol = "\n", na = "NA", dec = ".", row.names = TRUE,
            col.names = TRUE, qmethod = c("escape", "double"),
            fileEncoding = "")