2022-11-17 DiffBind使用

##安装DiffBind包

BiocManager::install("DiffBind")

library(DiffBind)

##准备samplelist.txt

##读入samplelist.txt

samples <- read.csv(file = "samplelist.txt", sep="\t")

##将其转化为后续分析用dba对象

obj <- dba(sampleSheet=samples)

view(obj)

##计数peaks上的reads

DBA_object <- dba.count(obj, bUseSummarizeOverlaps=TRUE)

view(DBA_object)

##PCA画图

pdf("PCA.pdf")

dba.plotPCA(DBA_object, attributes=DBA_CONDITION, label=DBA_ID)

dev.off()

##peaks热图

pdf("heatmap1.pdf")

plot(DBA_object)

dev.off()

##构建design和contrast模型

contrast <- dba.contrast(DBA_object, categories=DBA_CONDITION, minMembers =2)

view(contrast)

##差异分析

contrastResult <- dba.analyze(contrast, method=DBA_DESEQ2)

view(contrastResult)

dba.show(contrastResult, bContrast=T)

##简单可视化

pdf("CorandMA.pdf")

#plot(contrastResult, contrast=1) ####contrast=1指定dba.show(contrastResult, bContrast=T)的差异组合针对，特异差异组合进行相关性可视化

plot(contrastResult)

dba.plotMA(contrastResult)

dev.off()

##提取差异分析结果

Report <- dba.report(contrastResult, contrast=1)

view(Report)

result <- as.data.frame(Report)

write.table(result, file = "DX8HvsTGYDM.txt", sep="\t", quote=F, col.names = NA)

##统计一下上调、下调Peaks数量

sum(Report$Fold > 1)

sum(Report$Fold < -1)

##针对指定差异组合进行热图展示

pdf("heatmaptest.pdf")

hmap <- colorRampPalette(c("red","black","green"))(n = 13)

#dba.plotHeatmap(contrastResult, contrast=1, correlation=FALSE,scale="row",colScheme = hmap)####contrast=1指定dba.show(contrastResult, bContrast=T)的差异组合针对，特异差异组合进行

dba.plotHeatmap(contrastResult,correlation=FALSE,scale="row",colScheme = hmap)

dev.off()

引用：

https://www.jianshu.com/p/b74c8077d893