| Version: | 1.2 |
| Date: | 2025-05-14 |
| Title: | High Throughput 'GoMiner' |
| Maintainer: | Barry Zeeberg <barryz2013@gmail.com> |
| Author: | Barry Zeeberg [aut, cre] |
| Depends: | R (≥ 4.2.0) |
| Imports: | minimalistGODB, GoMiner, grDevices, stats, gplots, vprint |
| LazyData: | true |
| LazyDataCompression: | xz |
| Description: | Two papers published in the early 2000's (Zeeberg, B.R., Feng, W., Wang, G. et al. (2003) <doi:10.1186/gb-2003-4-4-r28>) and (Zeeberg, B.R., Qin, H., Narashimhan, S., et al. (2005) <doi:10.1186/1471-2105-6-168>) implement 'GoMiner' and 'High Throughput GoMiner' ('HTGM') to map lists of genes to the Gene Ontology (GO) https://geneontology.org. Until recently, these were hosted on a server at The National Cancer Institute (NCI). In order to continue providing these services to the bio-medical community, I have developed stand-alone versions. The current package 'HTGM' builds upon my recent package 'GoMiner'. The output of 'GoMiner' is a heatmap showing the relationship of a single list of genes and the significant categories into which they map. 'High Throughput GoMiner' ('HTGM') integrates the results of the individual 'GoMiner' analyses. The output of 'HTGM' is a heatmap showing the relationship of the significant categories derived from each gene list. The heatmap has only 2 axes, so the identity of the genes are unfortunately "integrated out of the equation." Because the graphic for the heatmap is implemented in Scalable Vector Graphics (SVG) technology, it is relatively easy to hyperlink each picture element to the relevant list of genes. By clicking on the desired picture element, the user can recover the "lost" genes. |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| Encoding: | UTF-8 |
| VignetteBuilder: | knitr |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
| RoxygenNote: | 7.3.2 |
| Config/testthat/edition: | 3 |
| NeedsCompilation: | no |
| Packaged: | 2025-05-14 16:30:03 UTC; barryzeeberg |
| Repository: | CRAN |
| Date/Publication: | 2025-05-14 17:00:02 UTC |
HTGM
Description
driver to invoke GoMiner for multiple studies, and integrate the results in a categories versus study hyperlinked heatmap
Usage
HTGM(
title = NULL,
dir = tempdir(),
sampleLists,
GOGOA3,
ONT,
enrichThresh = 2,
countThresh = 5,
fdrThresh = 0.1,
nrand = 100,
mn = 2,
mx = 200,
opt = 0,
verbose = 1
)
Arguments
title |
character string descriptive title |
dir |
character string full pathname to the directory acting as result repository |
sampleLists |
list of character vector of user-supplied genes of interest |
GOGOA3 |
return value of subsetGOGOA() |
ONT |
c("molecular_function","cellular_component","biological_process") |
enrichThresh |
numerical acceptance threshold for enrichment passed to GoMiner |
countThresh |
numerical acceptance threshold for gene count passed to GoMiner |
fdrThresh |
numerical acceptance threshold for fdr passed to GoMiner |
nrand |
integer number of randomizations passed to GoMiner |
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 parameter passed to vprint() |
Value
returns the matrix of significant categories versus study
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")
# load("data/Housekeeping_Genes.RData")
sampleList<-unique(as.matrix(Housekeeping_Genes[,"Gene.name"]))
n<-nrow(sampleList)
sampleLists<-list()
# test the effect of random sampling of the entire gene set
# this can give an idea of the quality of the GoMiner results
# when the complete gene set is yet to be determined
sampleLists[["1"]]<-sampleList[sample(n,n/2)]
sampleLists[["2"]]<-sampleList[sample(n,n/2)]
sampleLists[["3"]]<-sampleList[sample(n,n/2)]
sampleLists[["4"]]<-sampleList[sample(n,n/2)]
sampleLists[["5"]]<-sampleList[sample(n,n/2)]
sampleLists[["ALL"]]<-sampleList
m<-HTGM(title=NULL,dir=tempdir(),sampleLists,GOGOA3,ONT="biological_process",
enrichThresh=2,countThresh=5,fdrThresh=0.10,nrand=100)
## End(Not run)
HTGM data set
Description
HTGM data set
Usage
data(Housekeeping_Genes)
htgmM
Description
generate FDR matrix of id versus cat
Usage
htgmM(l, fdrThresh)
Arguments
l |
list of return values of GoMiner() |
fdrThresh |
numerical acceptance threshold for fdr |
Value
returns numeric matrix m containing FDR values
Examples
# load("data/x_l.RData")
m<-htgmM(x_l,.1)
hyperGenes
Description
populate subdirectory of hyperlinked gene lists
Usage
hyperGenes(l, dir)
Arguments
l |
return value of GoMiner() |
dir |
character string containing path name of results directory |
Value
returns no value but has side effect of populating subdirectory of hyperlinked gene lists
Examples
# x_l<-load("data/x_l.RData")
dir<-tempdir()
print(dir)
hyperGenes(x_l,dir)
hyperlinks
Description
driver to add gene list hyperlinks to the HTGM heatmap
Usage
hyperlinks(s, rownames, colnames)
Arguments
s |
character path name of the file containing the HTGM svg |
rownames |
character vector of row names |
colnames |
character vector of column names |
Value
returns the path name of the file containing the hyperlinked HTGM svg
Examples
#load("data/x_rn.RData")
#load("data/x_cn.RData")
#load("data/x_svg.RData")
s<-system.file("extdata","x_htgm.svg",package="HTGM")
# need to avoid writing to "extdata"
dir<-tempdir()
file.copy(from=s, to=dir)
hyperlinkedFileName<-hyperlinks(sprintf("%s/%s",dir,"x_htgm.svg"),x_rn,x_cn)
print("hyperlinkedFileName")
print(hyperlinkedFileName)
pasteHyperlinks
Description
add gene list hyperlinks to the HTGM heatmap
Usage
pasteHyperlinks(str, c1, c2)
Arguments
str |
character a line from the svg that is to have a hyperlink inserted |
c1 |
character list of row names |
c2 |
character list of column names |
Value
returns a line of code to insert into svg
Examples
#load("data/x_svgr.RData")
#load("data/x_rnr.RData")
#load("data/x_cnc.RData")
hl<-pasteHyperlinks(x_svgr,x_rnr,x_cnc)
HTGM data set
Description
HTGM data set
Usage
data(x_cn)
HTGM data set
Description
HTGM data set
Usage
data(x_cnc)
HTGM data set
Description
HTGM data set
Usage
data(x_l)
HTGM data set
Description
HTGM data set
Usage
data(x_m)
HTGM data set
Description
HTGM data set
Usage
data(x_rn)
HTGM data set
Description
HTGM data set
Usage
data(x_rnr)
HTGM data set
Description
HTGM data set
Usage
data(x_svg)
HTGM data set
Description
HTGM data set
Usage
data(x_svgr)