由於經常需要涉及到TCGA數據的分析，我簡單的整理了一下數據批量下載的文件後綴。

cancer_name <- "SKCM"
output_path <- paste0("/home/wang/Documents/課題/data/zip/", cancer_name)
system(paste0("mkdir ", output_path))

axel_string <- paste0("axel -n 30 -o ", output_path, " ")
main_path <- paste0("http://gdac.broadinstitute.org/runs/stddata__2016_01_28/data/", cancer_name, "/20160128/gdac.broadinstitute.org_")

#gene
gene_path <- paste0(main_path, cancer_name, ".Merge_rnaseqv2__illuminahiseq_rnaseqv2__unc_edu__Level_3__RSEM_genes__data.Level_3.2016012800.0.0.tar.gz")
system(paste0(axel_string, gene_path))

#methylation
methylation_path <- paste0(main_path, cancer_name, ".Methylation_Preprocess.Level_3.2016012800.0.0.tar.gz")
system(paste0(axel_string, methylation_path))

#mutation
mutation_path <- paste0(main_path, cancer_name, ".Mutation_Packager_Calls.Level_3.2016012800.0.0.tar.gz")
system(paste0(axel_string, mutation_path))

#SCNA
SCNA_path <- paste0(main_path, cancer_name, ".Merge_snp__genome_wide_snp_6__broad_mit_edu__Level_3__segmented_scna_hg19__seg.Level_3.2016012800.0.0.tar.gz")
system(paste0(axel_string, SCNA_path))

#clinical
clinical_path <- paste0(main_path, cancer_name, ".Merge_Clinical.Level_1.2016012800.0.0.tar.gz")
system(paste0(axel_string, clinical_path))

#miRNA
miRNA_path <- paste0(main_path, cancer_name, ".Merge_mirnaseq__illuminahiseq_mirnaseq__bcgsc_ca__Level_3__miR_gene_expression__data.Level_3.2016012800.0.0.tar.gz")
system(paste0(axel_string, miRNA_path))

TCGA數據批量下載