methylRRA: Enrichment analysis after adjusting multiple p-values of each...
In methylGSA: Gene Set Analysis Using the Outcome of Differential Methylation

Description Usage Arguments Value References Examples

This function implements enrichment after adjusting multiple p-values of each gene by Robust Rank Aggregation.

methylRRA(cpg.pval, array.type = "450K", FullAnnot = NULL,
  group = "all", method = "ORA", sig.cut = 0.05, topDE = NULL,
  GS.list = NULL, GS.idtype = "SYMBOL", GS.type = "GO",
  minsize = 100, maxsize = 500)

`cpg.pval`	A named vector containing p-values of differential methylation test. Names should be CpG IDs.
`array.type`	A string. Either "450K" or "EPIC". Default is "450K". This argument will be ignored if FullAnnot is provided.
`FullAnnot`	A data frame provided by prepareAnnot function. Default is NULL.
`group`	A string. "all", "body", "promoter1" or "promoter2". Default is "all". If group = "body", only CpGs on gene body will be considered in methylRRA. If group = "promoter1" or group = "promoter2", only CpGs on promoters will be considered. Here is the definition of "body", "promoter1" and "promoter2" according to the annotation in IlluminaHumanMethylation450kanno.ilmn12.hg19 or IlluminaHumanMethylationEPICanno.ilm10b4.hg19. body: CpGs whose gene group correspond to "Body" or "1stExon" promoter1: CpGs whose gene group correspond to "TSS1500" or "TSS200" promoter2: CpGs whose gene group correspond to "TSS1500", "TSS200", "1stExon", or "5'UTR". If group = "all", all CpGs are considered regardless of their gene group.
`method`	A string. "ORA" or "GSEA". Default is "ORA"
`sig.cut`	A numeric value indicating FDR cut-off for significant gene in ORA. Default is 0.05. This argument will be ignored if topDE is provided or method = "GSEA" is used.
`topDE`	An integer. The top number of genes to be declared as significant after robust rank aggregation. This argument will be ignored if method = "GSEA" is used.
`GS.list`	A list. Default is NULL. If there is no input list, Gene Ontology is used. Entry names are gene sets names, and elements correpond to genes that gene sets contain.
`GS.idtype`	A string. "SYMBOL", "ENSEMBL", "ENTREZID" or "REFSEQ". Default is "SYMBOL".
`GS.type`	A string. "GO", "KEGG", or "Reactome". Default is "GO"
`minsize`	An integer. If the number of genes in a gene set is less than this integer, this gene set is not tested. Default is 100.
`maxsize`	An integer. If the number of genes in a gene set is greater than this integer, this gene set is not tested. Default is 500.

A data frame contains gene set tests results.

Kolde, Raivo, et al. Robust rank aggregation for gene list integration and meta-analysis. Bioinformatics 28.4 (2012): 573-580.

Phipson, B., Maksimovic, J., and Oshlack, A. (2015). missMethyl: an R package for analysing methylation data from Illuminas HumanMethylation450 platform. Bioinformatics, btv560.

Yu, Guangchuang, et al. clusterProfiler: an R package for comparing biological themes among gene clusters. Omics: a journal of integrative biology 16.5 (2012): 284-287.

Carlson M (2017). org.Hs.eg.db: Genome wide annotation for Human. R package version 3.5.0.

data(CpG2Genetoy)
data(cpgtoy)
data(GSlisttoy)
GS.list = GS.list[1:10]
FullAnnot = prepareAnnot(CpG2Gene)
res1 = methylRRA(cpg.pval = cpg.pval, FullAnnot = FullAnnot,
method = "ORA", GS.list = GS.list)
head(res1)