2019-03-24

#first part: install RTCGA pacakages
# Load the bioconductor installer. 
source("https://bioconductor.org/biocLite.R")
# Install the main RTCGA package
biocLite("RTCGA")
# Install the clinical and mRNA gene expression data packages
biocLite("RTCGA.clinical") ## 14Mb
#biocLite('RTCGA.rnaseq') ##  (612.6 MB)
biocLite("RTCGA.mRNA") ##  (85.0 MB)
#biocLite('RTCGA.mutations')  ## (103.8 MB)

all_TCGA_cancers=infoTCGA()
library(DT)
DT::datatable(all_TCGA_cancers)

library(RTCGA.mRNA)
expr <- expressionsTCGA(LGG.mRNA, BRCA.mRNA,
                        extract.cols = c("IDH1","BRCA1","BRCA2"))
expr
DT::datatable(expr)

exgene = "IDH1"
boxplotTCGA(expr,x = "dataset", y = exgene,
            legend.title = exgene, ylab = "Expression")

library(ggpubr)
ggboxplot(expr, x = "dataset", y = exgene,
          title = exgene, ylab = "Expression",
          color = "dataset", palette = "jco")

ggboxplot(expr, x = "dataset", y = c("IDH1", "BRCA1","BRCA2"),
          combine = TRUE, ylab = "Expression",
          color = "dataset", palette = "jco")

library(RTCGA.clinical)

survivalTCGA(
  LGG.clinical,
  BRCA.clinical,
  extract.cols = "admin.disease_code") -> 
  LGG_BRCA.clinical
DT::datatable(LGG_BRCA.clinical)
kmTCGA(LGG_BRCA.clinical, explanatory.names = "admin.disease_code",  
pval = TRUE)