ChAMP-package {ChAMP} | R Documentation

## ChAMP-Chip Analysis Methylation Pipeline

### Description

A pipeline that enables pre-processing of 450K or EPIC data, a selection of normalization methods and a bundle of analysis method including SVD checking, Batch effect correction, DMP, DMR, Block detection, Cell proportion detection, GSEA pathway detection, EpiMod module detection, and copy number variance detection. ChAMP provided a very comprehensive analysis pipeline for EPIC or 450K data set.

### Details

Package: | ChAMP
Type: | Package
Version: | 2.8.6
Date: | 2017-07-19
License: | GPL-3

The full analysis pipeline can be run with all defaults using champ.process() Alternatively, it can be run in steps using all functions separately.

### Author(s)

Yuan Tian, Tiffany Morris, Lee Stirling, Andy Feber, Andrew Teschendorff, Ankur Chakravarthy, Stephen Beck
Maintainer: Yuan Tian <champ450k@gmail.com>

### Examples

    	directory=system.file('extdata',package='ChAMPdata')
    	champ.process(directory=directory)
        ### run champ functions separately.
        myLoad <- champ.load(directory)
        myImpute <- champ.impute()
        champ.QC()
        myNorm <- champ.norm()
        champ.SVD()
        myCombat <- champ.runCombat()
        myDMP <- champ.DMP()
        myDMR <- champ.DMR()
        myBlock <- champ.Block()
        myGSEA <- champ.GSEA()
        myEpiMod <- champ.EpiMod()
        myCNA <- champ.CNA()
        myRefbase <- champ.refbase() ### for blood sample only

        CpG.GUI()
        QC.GUI()
        DMP.GUI()
        DMR.GUI()
        Block.GUI()

[Package ChAMP version 2.22.0 Index]