Do GSEA for DMP, DMR and other methylation data related results.

Description

This function would do GSEA on the results of champ functions like DMP and DMR. However users may also add individual CpGs and genes in it.

Usage

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    champ.GSEA(beta=myNorm,
               DMP=myDMP,
               DMR=myDMR,
               CpGlist=NULL,
               Genelist=NULL,
               arraytype="450K",
               adjPval=0.05)

Arguments

beta

A matrix of values representing the methylation scores for each sample (M or B). Better to be imputed and normalized data. (default = myNorm)

DMP

Results from champ.DMP() function. (default = myDMP)

DMR

Results from champ.DMR() function. (default = myDMR)

CpGlist

Apart from previous parameters, if you have any other CpGs list want to do GSEA, you can input them here as a list. (default = NULL)

Genelist

Apart from previous parameters, if you have any other Gene list want to do GSEA. you can inpute them here as a list. (default = NULL)

arraytype

Which kind of array your data set is? (default = "450K")

adjPval

Adjusted p value cutoff for all calculated GSEA result. (default = 0.05)

Value

Block

A data.frame contains all detected Blocks, with colnames as chr, start, end, value, area, cluster, indexStart, indexEnd, L, clusterL, p.value, fwer, p.valueArea, fwerArea. The result format is actually the same as Bumphunter, you may refer to Bumphunter packages to get more explaination about the result.

clusterInfo

When champ.Block() detection significant Blocks, a group of candidate Blocks would be detected out at first, this is the data frame of all candidate Blocks. The "TRUE" Blocks in above value are located in these candidate Blocks.

allCLID.v

The first step of detectiong methylation Blocks is to get each probes into a cluster(region). This value is the clustering result of each probes.

avbetaCL.m

The beta matrix for each cluster. The value is calculated by taking mean value of all probes located in each cluster.

posCL.m

Position of each cluster, which is calculated by average all probes' position in each cluster.

adjPval

P value cutoff for calculated GSEA results. (default = 0.05)

Author(s)

Yuan Tian

Examples

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    ## Not run: 
        myLoad <- champ.load(directory=system.file("extdata",package="ChAMPdata"))
        myNorm <- champ.norm()
        myDMP <- champ.DMP()
        myDMR <- champ.DMR()
        myGSEA <- champ.GSEA()
        
## End(Not run)

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