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: 1.10.2
Date: 2016-08-24
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

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	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()
    myRefFree <- champ.reffree()
    myRefbase <- champ.refbase() ### for blood sample only

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

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