inst/doc/analysis_diff_meth.R

In ELMER: Inferring Regulatory Element Landscapes and Transcription Factor Networks Using Cancer Methylomes

## ---- echo = FALSE,hide=TRUE, message=FALSE, warning=FALSE--------------------
library(ELMER.data)
library(ELMER)
library(DT)
library(dplyr)
library(BiocStyle)

## ----eval=TRUE, message=FALSE, warning = FALSE, results = "hide"--------------
mae <- get(load("mae.rda"))
sig.diff <- get.diff.meth(data = mae, 
                          group.col = "definition",
                          group1 =  "Primary solid Tumor",
                          group2 = "Solid Tissue Normal",
                          minSubgroupFrac = 0.2, # if supervised mode set to 1
                          sig.dif = 0.3,
                          diff.dir = "hypo", # Search for hypomethylated probes in group 1
                          cores = 1, 
                          dir.out ="result", 
                          pvalue = 0.01)

## ----eval=TRUE, message=FALSE, warning = FALSE--------------------------------
head(sig.diff)  %>% datatable(options = list(scrollX = TRUE))
# get.diff.meth automatically save output files. 
# - getMethdiff.hypo.probes.csv contains statistics for all the probes.
# - getMethdiff.hypo.probes.significant.csv contains only the significant probes which
# is the same with sig.diff
# - a volcano plot with the diff mean and significance levels
dir(path = "result", pattern = "getMethdiff")  

## ----eval=TRUE, message=FALSE, warning = FALSE,echo=FALSE---------------------
group1 <-  "Primary solid Tumor"
group2 <- "Solid Tissue Normal"
out <- readr::read_csv(dir(path = "result", pattern = "getMethdiff.hypo.probes.csv",full.names = TRUE))
TCGAbiolinks:::TCGAVisualize_volcano(x = as.data.frame(out)[,grep("Minus",colnames(out),value = T)],
                                         y = out$adjust.p, 
                                         title =  paste0("Volcano plot - Probes ",
                                                        "hypomethylated in ", group1, " vs ", group2,"\n"),
                                         filename = NULL,
                                         label =  c("Not Significant",
                                                    paste0("Hypermethylated in ",group1),
                                                    paste0("Hypomethylated in ",group1)),
                                         ylab =  expression(paste(-Log[10],
                                                                  " (FDR corrected P-values) [one tailed test]")),
                                         xlab =  expression(paste(
                                           "DNA Methylation difference (",beta,"-values)")
                                         ),
                                         x.cut = 0.3, 
                                         y.cut = 0.01)