## ----setup, include=FALSE------------------------------------------------ knitr::opts_chunk$set(echo = TRUE) knitr::opts_knit$set(progress = FALSE) ## ----message=FALSE, warning=FALSE, include=FALSE------------------------- library(TCGAbiolinks) library(SummarizedExperiment) library(dplyr) library(DT) ## ----results = 'hide', eval = FALSE, message=FALSE, warning=FALSE-------- # query <- GDCquery(project = "TCGA-GBM", # data.category = "Gene expression", # data.type = "Gene expression quantification", # platform = "Illumina HiSeq", # file.type = "normalized_results", # experimental.strategy = "RNA-Seq", # barcode = c("TCGA-14-0736-02A-01R-2005-01", "TCGA-06-0211-02A-02R-2005-01"), # legacy = TRUE) # GDCdownload(query, method = "api", chunks.per.download = 10) # data <- GDCprepare(query) ## ----message=FALSE, warning=FALSE, eval = FALSE-------------------------- # # Gene expression aligned against hg19. # datatable(as.data.frame(colData(data)), # options = list(scrollX = TRUE, keys = TRUE, pageLength = 5), # rownames = FALSE) # # Only first 100 to make render faster # datatable(assay(data)[1:100,], # options = list(scrollX = TRUE, keys = TRUE, pageLength = 5), # rownames = TRUE) # # rowRanges(data) ## ----results = 'hide', message=FALSE, warning=FALSE, eval = FALSE-------- # # Gene expression aligned against hg38 # query <- GDCquery(project = "TCGA-GBM", # data.category = "Transcriptome Profiling", # data.type = "Gene Expression Quantification", # workflow.type = "HTSeq - FPKM-UQ", # barcode = c("TCGA-14-0736-02A-01R-2005-01", "TCGA-06-0211-02A-02R-2005-01")) # GDCdownload(query) # data <- GDCprepare(query) ## ----message=FALSE, warning=FALSE, eval = FALSE-------------------------- # datatable(as.data.frame(colData(data)), # options = list(scrollX = TRUE, keys = TRUE, pageLength = 5), # rownames = FALSE) # # datatable(assay(data)[1:100,], # options = list(scrollX = TRUE, keys = TRUE, pageLength = 5), # rownames = TRUE) # # rowRanges(data)