change buildGOmap() parameter, #47

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: GOSemSim
 Type: Package
 Title: GO-terms Semantic Similarity Measures
-Version: 2.29.1
+Version: 2.29.1.001
 Authors@R: c( person(given = "Guangchuang", family = "Yu",             email = "[email protected]", role  = c("aut", "cre")),
               person(given = "Alexey",      family = "Stukalov",       email = "[email protected]",     role  = "ctb"),
               person(given= "Pingfan",      family = "Guo",            email = "[email protected]",       role  = "ctb"),
@@ -48,4 +48,4 @@ URL: https://yulab-smu.top/biomedical-knowledge-mining-book/
 BugReports: https://github.com/YuLab-SMU/GOSemSim/issues
 Packaged: 2012-08-29 06:44:50 UTC; root
 biocViews: Annotation, GO, Clustering, Pathways, Network, Software
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.0

NEWS.md

@@ -1,3 +1,7 @@
+# GOSemSim 2.29.1.001
+
++ update `buildGOmap()` parameter to consistent with `enricher()` and `GSEA()` (2024-02-06, Tue, #47)
+
 # GOSemSim 2.29.1
 
 + extend `godata()` to support passing a data.frame (can be output of `read.gaf()` or `read.blast2go()`) to 'annoDb' (2023-01-16, Tue)

R/GOSemSim-package.R

@@ -1,45 +1,5 @@
-##'Gene Ontology-based Sematic Similarity Measures
-##'
-##'Implementation of semantic similarity measures to estimate the functional
-##'similarities among Gene Ontology terms and gene products
-##'
-##'Quantitative measure of functional similarities among gene products is
-##'important for post-genomics study. and widely used in gene function
-##'prediction, cluster analysis and pathway modeling.  This package is designed
-##'to estimate the GO terms' and genes' semantic similarities.  Implemented five
-##'methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively.
-##'Support many species, including Anopheles, Arabidopsis, Bovine, Canine,
-##'Chicken, Chimp, E coli strain K12 and strain Sakai, Fly, Human, Malaria,
-##'Mouse, Pig, Rhesus, Rat, Worm, Xenopus, Yeast, Zebrafish.
-##'
-##'\tabular{ll}{ Package: \tab GOSemSim\cr Type: \tab Package\cr Version: \tab
-##'2.0.0\cr Date: \tab 09-11-2012\cr biocViews:\tab GO, Clustering, Pathways,
-##'Anopheles_gambiae, Arabidopsis_thaliana, Bos_taurus, Caenorhabditis_elegans,
-##'Canis_familiaris, Danio_rerio, Drosophila_melanogaster, Escherichia_coli,
-##'Gallus_gallus, Homo_sapiens, Mus_musculus, Pan_troglodytes,
-##'Plasmodium_falciparum, Rattus_norvegicus, Saccharomyces_cerevisiae,
-##'Streptomyces_coelicolor, Sus_scrofa, Xenopus_laevis\cr Depends:\tab \cr
-##'Imports: \tab methods, AnnotationDbi, GO.db\cr
-##'Suggests:\tab clusterProfiler, DOSE\cr
-##'License: \tab Artistic-2.0\cr }
-##'
-##'@name GOSemSim-package
-##'@aliases GOSemSim-package GOSemSim
-##'@docType package
-##'@author Guangchuang Yu
-##'
-##'Maintainer: Guangchuang Yu <guangchuangyu@@gmail.com>
-##'@seealso \code{\link{goSim}} \code{\link{mgoSim}} \code{\link{geneSim}}
-##'\code{\link{mgeneSim}} \code{\link{clusterSim}} \code{\link{mclusterSim}}
-##'@references Yu et al. (2010) GOSemSim: an R package for measuring semantic
-##'similarity among GO terms and gene products \emph{Bioinformatics} (Oxford,
-##'England), 26:7 976--978, April 2010. ISSN 1367-4803
-##'\url{http://bioinformatics.oxfordjournals.org/cgi/content/abstract/26/7/976}
-##'PMID: 20179076
-##'@keywords package
-NULL
-
-
+#' @keywords internal
+"_PACKAGE"
 
 
 

R/buildGOmap.R

@@ -1,30 +1,30 @@
 ##' Addding indirect GO annotation
 ##'
-##' provided by a data.frame of GENE (column 1), GO (column 2) and ONTOLOGY (optional) that
+##' provided by a data.frame of GO TERM (column 1), GENE (column 2) and ONTOLOGY (optional) that
 ##' describes GO direct annotation, 
 ##' this function will add indirect GO annotation of genes.
 ##' @title buildGOmap
-##' @param x data.frame with two or three columns of GENE, GO and ONTOLOGY (optional)
+##' @param TERM2GENE data.frame with two or three columns of GO TERM, GENE and ONTOLOGY (optional)
 ##' @return data.frame, GO annotation with direct and indirect annotation
 ##' @importMethodsFrom AnnotationDbi as.list
 ##' @importFrom GO.db GOMFANCESTOR
 ##' @importFrom GO.db GOBPANCESTOR
 ##' @importFrom GO.db GOCCANCESTOR
 ##' @export
 ##' @author Yu Guangchuang
-buildGOmap <- function(x) {
+buildGOmap <- function(TERM2GENE) {
     mfanc <- as.list(GOMFANCESTOR)
     ccanc <- as.list(GOCCANCESTOR)
     bpanc <- as.list(GOBPANCESTOR)
 
-    if (!'ONTOLOGY' %in% names(x)) {
+    if (!'ONTOLOGY' %in% names(TERM2GENE)) {
         anc <- c(mfanc, ccanc, bpanc)
-        res <- buildGOmap_internal(x, anc)
+        res <- buildGOmap_internal(TERM2GENE, anc)
         return(res)
     }
 
     anc <- list(MF=mfanc, CC=ccanc, BP=bpanc)
-    y <- split(x, x$ONTOLOGY)
+    y <- split(TERM2GENE, TERM2GENE$ONTOLOGY)
 
     res <- lapply(names(y), function(i) {
         d <- buildGOmap_internal(y[[i]], anc[[i]])
@@ -37,15 +37,14 @@ buildGOmap <- function(x) {
 
 ##' @importFrom stats setNames
 ##' @importFrom yulab.utils ls2df
-buildGOmap_internal <- function(y, anc) {
-    res <- setNames(anc[y$GO], y[,1]) |> 
+buildGOmap_internal <- function(TERM2GENE, anc) {
+    res <- setNames(anc[TERM2GENE[,1]], TERM2GENE[,2]) |> 
         ls2df() |>
         unique()
 
-    names(res) <- c(names(y)[1], "GO")
-    res <- res[res$GO != "all", ]
-
-    res <- rbind(y[, names(res)], res)
+    res <- setNames(res[, c(2,1)], names(TERM2GENE)[1:2])
+    res <- res[res[,1] != "all", ]
+    res <- rbind(TERM2GENE[,1:2], res)
     return(res)
 }