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

Description Usage Arguments Value Author(s) Examples

View source: R/champ.GSEA.R

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. There are three method are incoporated into champ.GSEA function here. One is old Fisher Exact Test method, which will used information downloaded from MSigDB and do fisher exact test to calculated the enrichment status for each pathways. And another method is "gometh" method, which will use missMethyl package to correct the inequality between number of genes and number of CpGs, then do GSEA. The third and newest method is Empirical Bayes (ebayes) method, which does not need DMP or DMR information, but would directly calculate global test across all CpGs then do GSEA. User may assign parameter "method" as "ebayes", "gometh" or "fisher" to choose which method they want to use.

Usage

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    champ.GSEA(beta=myNorm,
               DMP=myDMP[[1]],
               DMR=myDMR,
               CpGlist=NULL,
               Genelist=NULL,
               pheno=myLoad$pd$Sample_Group,
               method="fisher",
               arraytype="450K",
               Rplot=TRUE,
               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)

pheno

If use ebayes method, user needs to provide phenotype information to conduct global test. (default = myLoad$pd$Sample_Group)

method

Which method would be used to do GSEA?"gometh" or "fisher". (default = "gometh")

arraytype

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

Rplot

If gometh method was chosen, should Probability Weight plot will be plotted. More information please check gometh package. (default = TRUE)

adjPval

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

Value

For fisher Method:

Genelist

List of pathway we get by enriching genes onto annotation database.

nOVLAP

Number of genes overlapped in your significant gene list and annotated pathways.

OR

Odds Ratio calculated for each enrichment.

P-value

Significance calculated from fisher exact test.

adjPval

Adjusted P value from "BH" method.

Genes

Name of genes enriched in each pathway.

For gometh method, the returned value are:

category

GO pathway's index.

over_represented_pvalue

The p value for genes' over representing in this pathway.

under_represented_pvalue

The p value for genes' under representing in this pathway.(Not likely to be used)

numDEInCat

Numbers of Different Methylation Genes in this pathway.

numInCat

Numbers of all genes related to this pathway.

term

The short explaination for this pathway.

ontology over_represented_adjPvalue

The ajusted over representing p value with "BH" method. User may used this one to select qualitied Pathways.

For ebayes method:

nREP

Number of genes enriched in this pathway.

AUC

Area under curve from wilcox test.

P

P value detected for each pathway.

adjP

Adjusted P value for each pathway, using BH method.

Author(s)

Yuan Tian, Danyue Dong

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)

ChAMP documentation built on May 11, 2018, 6 p.m.