The EpiMethEx package is under submission on bioconductor (https://github.com/Bioconductor/Contributions/issues), to use it you can follow the instructions below.
R CMD build EpiMethEx
install.packages(path_to_file, repos = NULL, type="source")
Annotations <- data.frame(
ID = c("cg11663302","cg01552731", "cg09081385"),
Relation_to_UCSC_CpG_Island = c("Island","N_Shore","N_Shore"),
UCSC_CpG_Islands_Name = c("chr1:18023481-18023792","chr19:46806998-46807617",
"chr12:120972167-120972447"),
UCSC_RefGene_Accession = c("NM_001011722","NM_152794","NM_014868"),
Chromosome_36 = c("1","19","12"),
Coordinate_36 = c("17896255","51498747","119456453"),
UCSC_RefGene_Name = c("ARHGEF10L","HIF3A","RNF10"),
UCSC_RefGene_Group =c("Body","1stExon","TSS200"),
stringsAsFactors=FALSE)
Expressions <- data.frame(
'sample' = c("ARHGEF10L", "HIF3A", "RNF10"),
'TCGA-YD-A89C-06' = c(-0.746592469762, -0.753826336325, 0.4953280),
'TCGA-Z2-AA3V-06' = c(0.578807530238, -2.30662633632, 0.1023280),
'TCGA-EB-A3Y6-01' = c(-0.363492469762, -2.67922633632, -0.6147720),
'TCGA-EE-A3JA-06' = c(-2.97279246976, -3.61932633632, 0.02932801),
'TCGA-D9-A4Z2-01' = c(-0.128492469762, 0.679073663675, 0.4017280),
'TCGA-D3-A51G-06' = c(-0.4299925, -4.0626263, -1.0136720),
stringsAsFactors=FALSE)
Methylation <- data.frame(
'sample' = c("cg11663302", "cg01552731", "cg09081385"),
'TCGA-YD-A89C-06' = c(0.9856, 0.7681, 0.0407),
'TCGA-Z2-AA3V-06' = c(0.9863, 0.8551, 0.0244),
'TCGA-EB-A3Y6-01' = c(0.9876, 0.6473, 0.028),
'TCGA-EE-A3JA-06' = c(0.9826, 0.4587, 0.0343),
'TCGA-D9-A4Z2-01' = c(0.9881, 0.8509, 0.0215),
'TCGA-D3-A51G-06' = c(0.9774, 0.813, 0.0332),
stringsAsFactors=FALSE)
4.1 or use the "curatedTCGAData" package:
source("https://bioconductor.org/biocLite.R")
BiocInstaller::biocLite("curatedTCGAData")
library(curatedTCGAData)
library(MultiAssayExperiment)
Methylation <- curatedTCGAData(diseaseCode = "SKCM", assays = "Methylation", dry.run = F)
Expressions <- curatedTCGAData(diseaseCode = "SKCM", assays = "RNASeq2GeneNorm", dry.run = F)
it's most important to remember that curatedTCGAData doesn't allow to download dataset of Annotations,therefore it must be loaded manually through csv file or created ad hoc
4.2 or use the csv file:
Expression <- read.csv2("Expressions.csv", header = T,sep = ";",stringsAsFactors=FALSE)
Annotations <- read.csv2("Annotations.csv",header = T,sep = ";",stringsAsFactors=FALSE)
Methylation <- read.csv2("Methylation.csv",header = T,sep = ";",stringsAsFactors=FALSE)
R
library(EpiMethEx)
epimethex.analysis(Expressions, Annotations, Methylation, 1, 3, 2,TRUE, TRUE, FALSE)
To further evaluate the biological significance of the methylation hotspots involved in gene regulation mechanisms, is possible to filter EpiMethEx output with an additional R script (https://github.com/giupardeb/EpiMethEx-Filter)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.