ccGeneList-class: Class "ccGeneList"

In categoryCompare: Meta-analysis of high-throughput experiments using feature annotations

Description

This stores the actual gene lists and related information that will be used in categoryCompare.

Objects from the Class

Objects can be created by calls of the form new("ccGeneList", list)). ccGeneList is actually just an extension of R list objects. The input list should be a list of lists. See Details for more information.

Slots

fdr:

Object of class "numeric" The number of fdr runs to perform to account for different list sizes and term dependence

pvalueCutoff:

Object of class "numeric" Value used to determine whether or not a particular term is significant or not

ccType:

Object of class "character" What types of annotations to use. Currently supported ones include "BP", "MF", "CC" (from Gene Ontology) and "KEGG"

testDirection:

Object of class "character" Are you interested in "over" or "under" represented annotations

Methods

fdr

signature(object = "ccGeneList"): how many random runs to perform

fdr<-

signature(object = "ccGeneList"): change the number of random runs

pvalueCutoff

signature(object = "ccGeneList"): what is the pvalue to consider significant

pvalueCutoff<-

signature(object = "ccGeneList"): change the cutoff for significance

ccType

signature(object = "ccGeneList"): what type of annotations are going to be examined

ccType<-

signature(object = "ccGeneList"): change the type of annotations to examine

testDirection

signature(object = "ccGeneList"): query for "over" or "under" represented annotations

testDirection<-

signature(object = "ccGeneList"): change the type of representation ("over" or "under")

listNames

signature(object = "ccGeneList"): what are the names of the lists contained

Details

The input list should be a list of lists, with at least three sub-lists.

testList <- list(list1=list(genes='...',universe='...',annotation='...'), list2=list(...))

genes

: These are the gene identifiers of the genes that are of interest (differentially expressed genes)

universe

: All of the genes that were measured in this particular experiments (i.e. all the genes on the chip)

annotation

: What organism or chip do these ID's come from (e.g. "org.Hs.eg.db" for Human Entrez gene ID's, "hgu133a.db" for probe ID's from the Affymetrix U133A chip)

data

: A data-frame that contains extra information about the genes of interest. At the very least, the data-frame must have a column ID that matches the ID's contained in genes

What actually happens when running ccEnrich is that the appropriate HyperGParamsCC objects are generated for each geneList and each type of annotation (e.g. BP, CC, KEGG), and then the calculations performed on each one.

Note

The ccGeneList object is what will undergo all of the enrichment calculations. When the results are combined with the ccOptions object, we can get our results of actual comparisons between experiments.

Author(s)

Robert M Flight

See Also

ccOptions

Examples

data(ccData)
g10 <- (unique(table10$Entrez[1:100]))
g48 <- (unique(table48$Entrez[1:100]))

list10 <- list(genes=g10, universe=gUniverse, annotation="org.Hs.eg.db")
list48 <- list(genes=g48, universe=gUniverse, annotation="org.Hs.eg.db")

geneLists <- list(T10=list10, T48=list48)
geneLists <- new("ccGeneList", geneLists, ccType=c("BP","KEGG"))
geneLists

categoryCompare documentation built on Nov. 8, 2020, 5:59 p.m.