appendGSTerms {HTSanalyzeR} | R Documentation |
This is a generic function.
When implemented as the S4 method for objects of class GSCA
,
this function finds corresponding annotation terms for KEGG and GO gene sets
and inserts a column named "Gene.Set.Term" to each data frame in the GSCA results.
To use this function for objects of class GSCA
:
appendGSTerms(object, keggGSCs=NULL, goGSCs=NULL)
appendGSTerms(object, ...)
object |
an object. When this function is implemented as the S4 method of class 'GSCA', this argument is an object of class 'GSCA'. |
... |
other arguments depending on class (see below for the arguments supported by the method of class 'GSCA') |
a character vector of names of all KEGG gene set collections
a character vector of names of all GO gene set collections
This function makes the GSCA results more readable by appending a column of terms for KEGG and GO gene sets. To do this, the user needs to specify the names of the gene set collections based on KEGG and GO, respectively.
For each KEGG gene set, the species code in the KEGG id will be trimmed off, and
then mapped to its corresponding annotation term using the function mget
of
the package AnnotationDbi
.
For each GO gene set, the GO id will be mapped to corresponding GO term by
the function Term
of the package GO.db
.
In the end, this function will return an updated object of class GSCA
.
Xin Wang xw264@cam.ac.uk
## Not run: library(org.Dm.eg.db) library(KEGG.db) ##load data for enrichment analyses data("KcViab_Data4Enrich") ##select hits hits <- names(KcViab_Data4Enrich)[which(abs(KcViab_Data4Enrich) > 2)] ##set up a list of gene set collections PW_KEGG <- KeggGeneSets(species = "Dm") gscList <- list(PW_KEGG = PW_KEGG) ##create an object of class 'GSCA' gsca <- new("GSCA", listOfGeneSetCollections=gscList, geneList = KcViab_Data4Enrich, hits = hits) ##print gsca gsca ##do preprocessing (KcViab_Data4Enrich has already been preprocessed) gsca <- preprocess(gsca, species="Dm", initialIDs = "Entrez.gene", keepMultipleMappings = TRUE, duplicateRemoverMethod = "max", orderAbsValue = FALSE) ##print gsca again gsca ##do hypergeometric tests and GSEA gsca <- analyze(gsca, para = list(pValueCutoff = 0.05, pAdjustMethod = "BH", nPermutations = 1000, minGeneSetSize = 100,exponent = 1)) ##append Kegg and GO gene set terms gsca<-appendGSTerms(gsca, keggGSCs="PW_KEGG") ## End(Not run)