GoMiner: GoMiner

In GoMiner: Automate the Mapping Between a List of Genes and Gene Ontology Categories

GoMiner

Description

driver to generate heatmap

Usage

GoMiner(
  title = NULL,
  dir,
  sampleList,
  GOGOA3,
  ontology,
  enrichThresh = 2,
  countThresh = 5,
  pvalThresh = 0.1,
  fdrThresh = 0.1,
  nrand = 100,
  mn = 2,
  mx = 200,
  opt,
  verbose = 1
)

Arguments

title	character string descriptive title
dir	character string full pathname to the directory acting result repository
sampleList	character list of gene names
GOGOA3	return value of subsetGOGOA()
ontology	character string c("molecular_function", "cellular_component", "biological_process")
enrichThresh	numerical acceptance threshold for enrichment
countThresh	numerical acceptance threshold for gene count
pvalThresh	numerical acceptance threshold for pval
fdrThresh	numerical acceptance threshold for fdr
nrand	numeric number of randomizations to compute FDR
mn	integer param passed to trimGOGOA3, min size threshold for a category
mx	integer param passed to trimGOGOA3, max size threshold for a category
opt	integer 0:1 parameter used to select randomization method
verbose	integer vector representing classes

Details

modes of FDR estimation: opt=0 use original database with randomized geneLists opt=1 use original geneList with internally scrambled genes databases (uses randomGODB())

databases that can be used with the real geneList: these are explicitly passed as parameter to GoMiner() (1) original GOGOA3 (2) randomized version of GOGOSA GOGOA3R<-randomGODB(GOGOA3) (3) database containing a subset of the big hitters genes (randomGODB2driver()) attempts to compensate for the over-annotation of some genes, that might lead to false positive if gene G has a lot of mappings to categories, randomly sample G/category pairs to retain a reasonable number of them. e.g., reduce G from 100 category mappings to 7 category mappings, by omitting 93 of the mappings G/category mappings

Value

returns a matrix suitable to generate a heatmap

Examples

## Not run: 
# GOGOA3.RData is too large to include in the R package
# so I need to load it from a file that is not in the package.
# Since this is in a file in my own file system, I could not
# include this as a regular example in the package.
# you can generate it using the package 'minimalistGODB'
# or you can retrieve it from https://github.com/barryzee/GO/tree/main/databases
load("/Users/barryzeeberg/personal/GODB_RDATA/goa_human/GOGOA3_goa_human.RData")
l<-GoMiner("Cluster52",tempdir(),cluster52,
 GOGOA3=GOGOA3,ontology="biological_process",enrichThresh=2,
 countThresh=5,pvalThresh=0.10,fdrThresh=0.10,nrand=2,mn=2,mx=200,opt=0,verbose=1)
 
 # try out yeast database!
 load("/Users/barryzeeberg/personal/GODB_RDATA/sgd/GOGOA3_sgd.RData")
 # make sure this is in fact the database for the desired species
 GOGOA3$species
 # use database to find genes mapping to an interesting category
 cat<-"GO_0042149__cellular_response_to_glucose_starvation"
 w<-which(GOGOA3$ontologies[["biological_process"]][,"GO_NAME"]==cat)
 geneList<-GOGOA3$ontologies[["biological_process"]][w,"HGNC"]
 l<-GoMiner("YEAST",tempdir(),geneList,
  GOGOA3,ontology="biological_process",enrichThresh=2,
  countThresh=3,pvalThresh=0.10,fdrThresh=0.10,nrand=2,mn=2,mx=200,opt=0)

## End(Not run)

GoMiner documentation built on June 8, 2025, 1:29 p.m.