## ---- echo=FALSE------------------------------------------------------------------------------------------------------------------------------------
library(knitr)
opts_chunk$set(comment="", message=FALSE, warning = FALSE, tidy.opts=list(keep.blank.line=TRUE, width.cutoff=150), options(width=150), eval = FALSE)

## ---- eval=FALSE------------------------------------------------------------------------------------------------------------------------------------
#  source("http://bioconductor.org/biocLite.R")
#  biocLite("RTCGA")

## ---- eval=FALSE------------------------------------------------------------------------------------------------------------------------------------
#  if (!require(devtools)) {
#      install.packages("devtools")
#      require(devtools)
#  }
#  biocLite("RTCGA/RTCGA")

## ---- eval=FALSE------------------------------------------------------------------------------------------------------------------------------------
#  browseVignettes("RTCGA")

## ---- eval=FALSE------------------------------------------------------------------------------------------------------------------------------------
#  library(RTCGA)
#  checkTCGA('Dates')

## ---- eval=FALSE------------------------------------------------------------------------------------------------------------------------------------
#  (cohorts <- infoTCGA() %>%
#     rownames() %>%
#     sub("-counts", "", x=.))

## ---- eval=FALSE------------------------------------------------------------------------------------------------------------------------------------
#  # dir.create( "data2" ) # name of a directory in which data will be stored
#  releaseDate <- "2015-11-01"
#  sapply( cohorts, function(element){
#  tryCatch({
#  downloadTCGA( cancerTypes = element,
#                destDir = "data2",
#                date = releaseDate )},
#  error = function(cond){
#     cat("Error: Maybe there weren't clinical data for ", element, " cancer.\n")
#  }
#  )
#  })

## ---- eval=FALSE------------------------------------------------------------------------------------------------------------------------------------
#  list.files( "data2") %>%
#     file.path( "data2", .) %>%
#     file.rename( to = substr(.,start=1,stop=50))

## ---- eval=FALSE------------------------------------------------------------------------------------------------------------------------------------
#  list.files( "data2") %>%
#     file.path( "data2", .) %>%
#     sapply(function(x){
#        if (x == "data2/NA")
#           file.remove(x)
#     })

## ---------------------------------------------------------------------------------------------------------------------------------------------------
#  cohorts %>%
#  	sapply(function(z){
#  		list.files("data2") %>%
#  			file.path("data2", .) %>%
#  			grep(paste0("_",z,"\\."), x = ., value = TRUE) %>%
#  			file.path(., list.files(.)) %>%
#  			grep("clin.merged.txt", x = ., value = TRUE) %>%
#  			assign(value = .,
#  						 x = paste0(z, ".clinical.path"),
#  						 envir = .GlobalEnv)
#  	})

## ---- eval=FALSE------------------------------------------------------------------------------------------------------------------------------------
#  ls() %>%
#     grep("clinical\\.path", x = ., value = TRUE) %>%
#     sapply(function(element){
#        tryCatch({
#           readTCGA(get(element, envir = .GlobalEnv),
#                 dataType = "clinical") -> clinical_file
#           	
#  		     ## remove non-ASCII strings:
#  		     for( i in 1:ncol(clinical_file)){
#  		       clinical_file[, i] <- iconv(clinical_file[, i],
#  		                                    "UTF-8", "ASCII", sub="")
#  		     }
#           	
#           assign(value = clinical_file,
#                  x = sub("\\.path", "", x = element),
#                  envir = .GlobalEnv )
#        }, error = function(cond){
#           cat(element)
#        })
#       invisible(NULL)
#      }
#  )

## ---- eval=FALSE------------------------------------------------------------------------------------------------------------------------------------
#  grep( "clinical", ls(), value = TRUE) %>%
#     grep("path", x=., value = TRUE, invert = TRUE) %>%
#     cat( sep="," ) #can one to it better? as from use_data documentation:
#     # ...	Unquoted names of existing objects to save
#     devtools::use_data(ACC.clinical,BLCA.clinical,BRCA.clinical,
#     									 CESC.clinical,CHOL.clinical,COAD.clinical,
#     									 COADREAD.clinical,DLBC.clinical,ESCA.clinical,
#     									 FPPP.clinical,GBM.clinical,GBMLGG.clinical,
#     									 HNSC.clinical,KICH.clinical,KIPAN.clinical,
#     									 KIRC.clinical,KIRP.clinical,LAML.clinical,
#     									 LGG.clinical,LIHC.clinical,LUAD.clinical,
#     									 LUSC.clinical,MESO.clinical,OV.clinical,
#     									 PAAD.clinical,PCPG.clinical,PRAD.clinical,
#     									 READ.clinical,SARC.clinical,SKCM.clinical,
#     									 STAD.clinical,STES.clinical,TGCT.clinical,
#     									 THCA.clinical,THYM.clinical,UCEC.clinical,
#     									 UCS.clinical,UVM.clinical,
#                        compress="xz")