GSVA计算基因样本的相似性

喜欢ヅ旅行 2022-02-13 11:21 240阅读 0赞

## 下载包 ##

# source('http://bioconductor.org/biocLite.R')
    # options(BioC_mirror='http://mirrors.ustc.edu.cn/bioc/')
    # biocLite('estimate')
    # library(GSVA)
    # browseVignettes('GSVA')
    # browseVignettes('estimate')
    
    
    source("http://www.bioconductor.org/biocLite.R") 
    options(BioC_mirror="http://mirrors.ustc.edu.cn/bioc/",repos=structure(c(CRAN="http://mirrors.tuna.tsinghua.edu.cn/CRAN/")))
    # biocLite('GSVA')
    # biocLite('GSVAdata')
    # biocLite('genefilter')
    # biocLite('limma')
    # biocLite('edgeR')
     
    
    
    #browseVignettes('GSVA') #get the GSVA code
    # browseVignettes('estimate')

## 加载调用包 ##

library(BiocGenerics)
    library(parallel)
    library(Biobase)
    library(annotate)
    library(AnnotationDbi)
    library(stats4)
    library(IRanges)
    library(S4Vectors)
    library(XML)
    library(graph)
    library(GSEABase)
    
    library(Biobase)
    library(genefilter)
    library(limma)
    library(RColorBrewer)
    library(org.Hs.eg.db)
    library(hgu95a.db)
    library(GSVAdata)
    library(GSVAdata)
    library(GSVA)

## 表达式数据转换 ##

# input=read.table("FULLDATA.csv", header=TRUE, row.names="id", sep = ",")
    # esete <- as.matrix(input)
    # group<-read.csv("group.csv", row.names="sampleID", sep=",")
    # metaData <- data.frame(labelDescription=c("group"),row.names=c("group"))
    # AnnotatedDataFrame()
    # AnnotatedDataFrame(data=group)
    # AnnotatedDataFrame(data=group, varMetadata=metaData)
    # anno <- as(group, "AnnotatedDataFrame")
    # ExpressionSet()
    # exset <- ExpressionSet(esete,anno)

## 绘制图形 ##

（代码略）图形类似  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3RhbmRlbGlu_size_16_color_FFFFFF_t_70]

[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3RhbmRlbGlu_size_16_color_FFFFFF_t_70]: /images/20220213/db206979046a4c0abfc91f40b9dc852e.png