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coMET (version 1.2.0)

coMET-package: visualisation of regional epigenome-wide association scan (EWAS) results and DNA co-methylation patterns (and also for other omic-WAS)

Description

coMET is an R package for visualising EWAS results in a genomic region. Along with phenotype-association plots, coMET also generates plots of co-methylation patterns and provides a series of annotation tracks. The software is designed for epigenetic data, but can also be applied to genomic and functional genomic datasets (other omic-WAS results) in any species.

Arguments

Details

Package:
coMET
Type:
Package
Version:
0.99.10
Date:
2015-04-10
License:
GPL (>=2)
coMET is an R package that can generate regional plots of EWAS results, DNA co-methylation patterns, and genomic information. A coMET figure includes 3 panels with a plot of P-values from EWAS, customized annotation tracks, and a triangle heatmap plot which demonstrates the correlation structure of DNA methylation at the CpG sites in the genomic region. Plots are created as PDF or EPS files.

References

Martin, T.C, Erte, I, Tsai, P-C, Bell, J.T., coMET: an R plotting package to visualize regional plots of epigenome-wide association scan results, QG14, 2014.

Examples

Run this code

extdata <- system.file("extdata", package="coMET",mustWork=TRUE)
configfile <- file.path(extdata, "config_cyp1b1_zoom_4comet.txt") 
myinfofile <- file.path(extdata, "cyp1b1_infofile.txt")
myexpressfile <- file.path(extdata, "cyp1b1_infofile_exprGene_region.txt")
mycorrelation <- file.path(extdata, "cyp1b1_res37_rawMatrix.txt")

chrom <- "chr2"
start <- 38290160
end <- 38303219
gen <- "hg19"

if(interactive()){
    genetrack <-genesENSEMBL(gen,chrom,start,end,showId=TRUE)
    snptrack <- snpBiomart(chrom, start, end, 
                    dataset="hsapiens_snp_som",showId=FALSE)
    strutrack <- structureBiomart(chrom, start, end, 
                    strand, dataset="hsapiens_structvar_som")
    clinVariant<-ClinVarMainTrack(gen,chrom,start,end)
    clinCNV<-ClinVarCnvTrack(gen,chrom,start,end)
    gwastrack <-GWASTrack(gen,chrom,start,end)
    geneRtrack <-GeneReviewsTrack(gen,chrom,start,end)

    listgviz <- list(genetrack,snptrack,strutrack,clinVariant,
                    clinCNV,gwastrack,geneRtrack)
                    
    comet(config.file=configfile, mydata.file=myinfofile,  mydata.type="listfile",
         cormatrix.file=mycorrelation, cormatrix.type="listfile",
         mydata.file=myexpressfile, mydata.large.type="listfile",
         tracks.gviz=listgviz, 
         verbose=FALSE, print.image=FALSE,disp.pvalueplot=TRUE)
} else {
    data(geneENSEMBLtrack)
    data(snpBiomarttrack)
    data(ISCAtrack)
    data(strucBiomarttrack)
    data(ClinVarCnvTrack)
    data(clinVarMaintrack)
    data(GWASTrack)
    data(GeneReviewTrack)

    listgviz <- list(genetrack,snptrack,strutrack,clinVariant,
                    clinCNV,gwastrack,geneRtrack)
    comet(config.file=configfile, mydata.file=myinfofile, mydata.type="listfile",
        cormatrix.file=mycorrelation, cormatrix.type="listfile",
        mydata.large.file=myexpressfile, mydata.large.type="listfile",
        tracks.gviz=listgviz, 
        verbose=FALSE, print.image=FALSE,disp.pvalueplot=TRUE)
}

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