coMET-package {coMET} | R Documentation

## 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.

### Details

Package: | coMET
Type: | Package
Version: | 1.11.5
Date: | 2018-04-16
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.

### Author(s)

Tiphaine C. Martin, Thomas Hardiman, Idil Yet, Pei-Chien Tsai, Jordana T. Bell

Maintainer: Tiphaine Martin <tiphaine.martin@mssm.edu>

Website: http://www.epigen.kcl.ac.uk/comet

### References

Martin, T.C, Yet, I, Tsai, P-C, Bell, J.T., coMET: visualisation of regional epigenome-wide association scan results and DNA co-methylation patterns, BMC bioinformatics, 2015.

### Examples

    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 <- "hg38"

    if(interactive()){
        genetrack <-genes_ENSEMBL(gen,chrom,start,end,showId=TRUE)
        snptrack <- snpBiomart_ENSEMBL(gen, chrom, start, end,
                    dataset="hsapiens_snp_som",showId=FALSE)
        strutrack <- structureBiomart_ENSEMBL(gen, chrom, start, end,
                    strand, dataset="hsapiens_structvar_som")
        clinVariant<-ClinVarMain_UCSC(gen,chrom,start,end)
        clinCNV<-ClinVarCnv_UCSC(gen,chrom,start,end)
        gwastrack <-GWAScatalog_UCSC(gen,chrom,start,end)
        geneRtrack <-GeneReviews_UCSC(gen,chrom,start,end)
        listgviz <- list(genetrack,snptrack,strutrack,clinVariant,
                     clinCNV,gwastrack,geneRtrack)
        comet(config.file=configfile, mydata.file=myinfofile, mydata.type="file",
          cormatrix.file=mycorrelation, cormatrix.type="listfile",
          mydata.large.file=myexpressfile, mydata.large.type="listfile",
          tracks.gviz=listgviz, verbose=FALSE, print.image=FALSE,disp.pvalueplot=FALSE)
    } 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)
    }

[Package coMET version 1.26.0 Index]