diff --git a/DESCRIPTION b/DESCRIPTION
index 0748244d58bd16fc5e3bf080f0e63ec66e373f85..dbb17b0fe90fbb7a8792091335515bc0e7c5a3db 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,5 +1,5 @@
Package: ViSEAGO
-Version: 1.3.6
+Version: 1.3.7
Title: ViSEAGO: a Bioconductor package for clustering biological functions using Gene Ontology and semantic similarity
Author: Aurelien Brionne [aut, cre],
Amelie Juanchich [aut],
diff --git a/NEWS b/NEWS
index 4f5f07d374895eac98ab9c5de6a8c5e00ad5c951..c13d218427eed8a98f631ddf3ef79539ff12342f 100644
--- a/NEWS
+++ b/NEWS
@@ -72,4 +72,5 @@ CHANGES IN VERSION 1.3
o show_heatmap() upgrade
o upset print update
o merge_enrich_terms upgrade pvalue cutoff
+ o merge_enrich_terms globale upgrade
diff --git a/R/merge_enrich_terms.R b/R/merge_enrich_terms.R
index 27e29f6eccd7ee19800e774aea9838f377d79ebb..0c06c275d9e43c382d0acb77e42a37a9b4b15f6c 100644
--- a/R/merge_enrich_terms.R
+++ b/R/merge_enrich_terms.R
@@ -151,7 +151,7 @@ setMethod(
unlist(
lapply(seq_along(Input),function(x){
- # extract quering objects names
+ # extract quering objects names
x=Input[[x]]
# check existence
@@ -160,7 +160,7 @@ setMethod(
# check if available
available<-x%in%values
- # stop if not
+ # stop if not found
if(!all(available)){
stop(paste("objects not found:",paste(x[!available],collapse=", "),sep="\n"))
}
@@ -193,7 +193,7 @@ setMethod(
# check ontology
if(length(check.onto)>1){
- # stop if more than one godata by list
+ # stop if more than one topGOdata by list
stop("Only one ontology supported")
}
@@ -312,34 +312,25 @@ setMethod(
}
# objects type
- if(sum(obj.type%in%"topGOresult")<1){
+ if(sum(obj.type%in%"topGOresult")>1){
# stop if more than one godata by list
- stop("At least one topGOresult object needed by list")
+ stop("Only one topGOresult object is supported by list")
}
## find and extract pvalues
- # load GOdata
+ # find topGOresult
pos=which(obj.type=="topGOresult")
- # tested algorithm
- algorithms<-Data[pos]
-
- # extract significant pvalues results
- unlist(
- lapply(algorithms,function(y){
-
- # extract scores
- pvalues<-topGO::score(y)
-
- # extract names of enrich terms
- as.vector(
- names(
- pvalues[pvalues<as.numeric(sub("^.+[[:space:]]","",slot(y,"testName")))]
- )
- )
- })
+ # extract scores
+ pvalues<-topGO::score(Data[[pos]])
+
+ # extract names of enrich terms
+ as.vector(
+ names(
+ pvalues[pvalues<as.numeric(sub("^.+[[:space:]]","",slot(Data[[pos]],"testName")))]
+ )
)
})
@@ -400,7 +391,7 @@ setMethod(
GOdata=Data[[pos]]
# tested algorithm
- algorithms<-Data[-pos]
+ algorithm<-Data[-pos]
## extract some statistics from initial GOdata object (before enrichment test)
@@ -680,47 +671,21 @@ setMethod(
## extract pvalue according the algorithm results
- # extract pvalues results
- pvalues<-lapply(seq_along(algorithms),function(y){
-
- # extract all pvalues from topGOresult
- pvalue<-topGO::score(algorithms[[y]])
-
- # select pvalues from topGOresult
- pvalue<-pvalue[GOs]
-
- # extract pvalue in data.table
- pvalue<-data.table(
- GO.ID=names(pvalue),
- pvalue=as.numeric(format(pvalue,scientific = T)),
- round(-log10(pvalue),digits=2)
- )
-
- # ordering pvalue by go term
- names(pvalue)[ncol(pvalue)]="-log10_pvalue"
-
- if(y>1){
-
- # remove GO.ID
- pvalue[,"GO.ID":=NULL]
- }
-
- # return
- pvalue
- })
-
- # convert to data.table
- pvalues=data.table(do.call("cbind",pvalues))
-
- # algoritms
- algo=vapply(algorithms,function(x){slot(x,"algorithm")},"")
-
- # if use of different algorithms
- if(length(algo)>1){
+ # extract all pvalues from topGOresult
+ pvalue<-topGO::score(algorithm[[1]])
+
+ # select pvalues from topGOresult
+ pvalue<-pvalue[GOs]
+
+ # extract pvalue in data.table
+ pvalues<-data.table(
+ GO.ID=names(pvalue),
+ pvalue=as.numeric(format(pvalue,scientific = T)),
+ `-log10_pvalue`=round(-log10(pvalue),digits=2)
+ )
- # add names
- names(pvalues)[-1]<-paste(rep(algo,each=2),names(pvalues)[-1],sep=".")
- }
+ # algorithm
+ algo=slot(algorithm[[1]],"algorithm")
# return input params
assign(
@@ -756,29 +721,19 @@ setMethod(
Results<-Results[!is.na(Results$GO.ID)]
# extract pvalue threshold
- p<-unique(vapply(algorithms,function(x){ as.numeric(sub("^.+[[:space:]]","",slot(x,"testName")))},0))
-
- # stop if more than one pvalue threshold among comparison
- if(length(p)>1){stop("Only one pvalue theshold is allowed by list element.")}
+ p<-as.numeric(sub("^.+[[:space:]]","",slot(algorithm[[1]],"testName")))
# Remove gene ID and symbol if GO term not significant
Results[Results$pvalue>=p,`:=`(Significant_genes=NA,Significant_genes_symbol=NA)]
if(!is.null(names(Input))){
- # add GOdata name
- if(x==1){
-
- # add GOdata name in the header
- names(Results)[-1]<-paste(names(Input)[x],
- names(Results)[-1],sep=".")
-
- }else{
-
- # add GOdata name in the header
- names(Results)[-1]<-paste(names(Input)[x],
- names(Results)[-1],sep=".")
- }
+ # add GOdata name in the header
+ names(Results)[-1]<-paste(
+ names(Input)[x],
+ names(Results)[-1],
+ sep="."
+ )
}
# return Results
diff --git a/README.md b/README.md
index 5c35505414b87a0a434c7c79c08461f472fbe181..6c2ce311424e9ef4dda85af7aad1e074d5b7c8c7 100644
--- a/README.md
+++ b/README.md
@@ -27,7 +27,7 @@ remotes::install_gitlab(
devtools::build("ViSEAGO")
# install package (from R console)
- install.packages("ViSEAGO_1.3.6.tar.gz", repos = NULL, type = "source")
+ install.packages("ViSEAGO_1.3.7.tar.gz", repos = NULL, type = "source")
```
## Citation
diff --git a/vignettes/mouse_bionconductor.Rmd b/vignettes/mouse_bionconductor.Rmd
index c9ff44ecc3a010b45ae8d33ad6f989b722e449c1..f72292131fe6614183adde2e2c9b34de3d35afde 100644
--- a/vignettes/mouse_bionconductor.Rmd
+++ b/vignettes/mouse_bionconductor.Rmd
@@ -174,7 +174,7 @@ BP_VirginvsPregnant<-ViSEAGO::create_topGOdata(
)
```
-Now, we perform the GO enrichment tests for BP category with Fisher's exact test and *elim* algorithm using `topGO::runTest` method.
+Now, we perform the GO enrichment tests for BP category with Fisher's exact test and *elim* algorithm using `topGO::runTest` method.
<u>NB</u>: p-values of enriched GO terms are not adjusted and considered significant if below 0.01.
@@ -209,8 +209,7 @@ The printed table contains for each enriched GO terms, additional columns includ
```{r Enrichment_merge}
# merge topGO results
-ViSEAGO::
-BP_sResults<-merge_enrich_terms(
+BP_sResults<-ViSEAGO::merge_enrich_terms(
Input=list(
PregnantvsLactate=c(
"BP_PregnantvsLactate",