methyDiff_ucsc: Title

In GeoTcgaData: Processing various types of data on GEO and TCGA

Title

Description

Title

Usage

methyDiff_ucsc(
  methy,
  sampleGroup = NULL,
  missing_value = "knn",
  model = c("cpg", "gene"),
  combineMethod = RobustRankAggreg::rhoScores,
  region = "Body"
)

Arguments

methy	data.frame of the methylation data, which can be downloaded from UCSC Xena.
sampleGroup	a vector of "0" and "1" for group of samples. If null, the samples were divided into two groups: disease and normal.
missing_value	Method to impute missing expression data, one of "zero" and "knn".
model	if "cpg", step1: calculate difference cpgs; step2: calculate difference genes. if "gene", step1: calculate the methylation level of genes; step2: calculate difference genes.
combineMethod	method to combine the cpg pvalues.
region	region of genes, one of "Body", "TSS1500", "TSS200", "3'UTR", "1stExon", "5'UTR", and "IGR".

Examples

## Not run: 
methy_file <- "TCGA.THCA.sampleMap_HumanMethylation450.gz"
methy <- data.table::fread(methy_file, sep = "\t", header = T)
library(ChAMP)
myImport <- champ.import(directory=system.file("extdata",package="ChAMPdata"))
myfilter <- champ.filter(beta=myImport$beta,pd=myImport$pd,
    detP=myImport$detP,beadcount=myImport$beadcount)
cpg_gene <- hm450.manifest.hg19[, c("probeID", "gene_HGNC")]
result <- methyDiff_ucsc(methy, cpg_gene)

## End(Not run)

GeoTcgaData documentation built on Sept. 23, 2022, 9:05 a.m.