前言

之前一直在用RTCGA包下载数据，看着永不更新的数据，心里总觉得怪怪的，于是下定决心重新学习一个好用的包——TCGAbiolinks。这个包调用GDC的API，应该是最新的数据。
主要参考：TCGAbiolinks: TCGAbiolinks: An R/Bioconductor package for integrative analysis with GDC data

下载数据

直接上代码

# if (!requireNamespace("BiocManager", quietly=TRUE))#   install.packages("BiocManager")# BiocManager::install("TCGAbiolinks") library(TCGAbiolinks)library(dplyr)library(DT)library(SummarizedExperiment)#下面填入要下载的癌症种类request_cancer=c("PRAD","BLCA","KICH","KIRC","KIRP")for (i in request_cancer) {  cancer_type=paste("TCGA",i,sep="-")  print(cancer_type)  #下载临床数据  clinical <- GDCquery_clinic(project = cancer_type, type = "clinical")  write.csv(clinical,file = paste(cancer_type,"clinical.csv",sep = "-"))    #下载rna-seq的counts数据  query <- GDCquery(project = cancer_type,                     data.category = "Transcriptome Profiling",                     data.type = "Gene Expression Quantification",                     workflow.type = "HTSeq - Counts")    GDCdownload(query, method = "api", files.per.chunk = 100)  expdat <- GDCprepare(query = query)  count_matrix=assay(expdat)  write.csv(count_matrix,file = paste(cancer_type,"Counts.csv",sep = "-"))    #下载miRNA数据  query <- GDCquery(project = cancer_type,                     data.category = "Transcriptome Profiling",                     data.type = "miRNA Expression Quantification",                     workflow.type = "BCGSC miRNA Profiling")    GDCdownload(query, method = "api", files.per.chunk = 50)  expdat <- GDCprepare(query = query)  count_matrix=assay(expdat)  write.csv(count_matrix,file = paste(cancer_type,"miRNA.csv",sep = "-"))    #下载Copy Number Variation数据  query <- GDCquery(project = cancer_type,                     data.category = "Copy Number Variation",                     data.type = "Copy Number Segment")    GDCdownload(query, method = "api", files.per.chunk = 50)  expdat <- GDCprepare(query = query)  count_matrix=assay(expdat)  write.csv(count_matrix,file = paste(cancer_type,"Copy-Number-Variation.csv",sep = "-"))    #下载甲基化数据  query.met <- GDCquery(project =cancer_type,                        legacy = TRUE,                        data.category = "DNA methylation")  GDCdownload(query.met, method = "api", files.per.chunk = 300)  expdat <- GDCprepare(query = query)  count_matrix=assay(expdat)  write.csv(count_matrix,file = paste(cancer_type,"methylation.csv",sep = "-"))}

常用的一些数据基本都下下来了，放在当前目录下。

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