diff --git a/DESCRIPTION b/DESCRIPTION
index b1c6d328376683c603eaefd4b48bc5e4a3203497..d76ead64b84b0545741a6dfb41506636a2fb6335 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,10 +1,11 @@
 Package: coGSEA
 Title: coGSEA : comparison of Gene Set Enrichment Analysis methods
-Version: 0.0.0.9000
+Version: 0.0.1
 Authors@R: person("Maxime", "Borry", email = "maxime.borry@gmail.com", role = c("aut", "cre"))
 Description: comparison of GSEA methods on the ranks and pvalues of genesets. Largely inspired (and contains some code) by eGSEA package.
 License: MIT
 Encoding: UTF-8
+LazyData: false
 Depends:
 	R (>= 3.3.3),
 	parallel,
diff --git a/R/comparResumPlot.r b/R/comparResumPlot.r
new file mode 100644
index 0000000000000000000000000000000000000000..007ce1d8488c61104429b9e9315db5066019ad1d
--- /dev/null
+++ b/R/comparResumPlot.r
@@ -0,0 +1,10 @@
+
+#' Internal function for coGSEA
+#'
+#' @export
+
+comparResumPlot = function(preparedData, savePlot = TRUE, legend = TRUE, directoryPath = directoryPath){
+    print("Plotting Summary comparison Plot for all conditions")
+    generateSummaryPlots(comparisonSummaryData(preparedData), savePlot = savePlot, legend = legend, file.name = paste(directoryPath, "_comparison_sumplot", sep = ""), format = "pdf")
+
+}
diff --git a/R/generateSummaryPlots.r b/R/generateSummaryPlots.r
index 4a05c170a88584b1365fb527131c6f82d84dac6b..bc6a86f892573594eed8c64613e7adbf99ef6f85 100644
--- a/R/generateSummaryPlots.r
+++ b/R/generateSummaryPlots.r
@@ -7,6 +7,7 @@
 #' @param Ybal  label for Y axis (character)
 #' @param firstN  N number of top N genes to highlight in blue (integer)
 #' @param savePlot  Wheter to save the plot, or just display it (boolean)
+#' @param legen whether to display or not the legend if savePlot = FALSE (boolean)
 
 #' @return A plot if savePlot = TRUE, else nothing
 #' @examples
@@ -16,7 +17,7 @@
 #' @export
 
 generateSummaryPlots <- function(plot.data, file.name = "resumPlot", Xlab="-log10(p-value)",
-        Ylab="Average Absolute logFC", format = NULL, firstN = 10,  savePlot = TRUE){
+        Ylab="Average Absolute logFC", format = NULL, firstN = 10,  savePlot = TRUE, legend = TRUE){
         if(!require(ggplot2)){
             install.packages("ggplot2")
             require(ggplot2)
@@ -116,11 +117,13 @@ name="Regulation Direction") # low="#5FE377"
                                 colour=sig.cols, vjust=-1, hjust=1) )
                 dev.off()
             }
-        } else {
-            p + geom_text(size=5, mapping=aes(x=x.data, y=y.data,
+        } else if (savePlot == FALSE && legend == TRUE){
+            print(p + geom_text(size=5, mapping=aes(x=x.data, y=y.data,
                             label=id),
                             data=plot.data.sig,
-                            colour=sig.cols, vjust=-1, hjust=1)
+                            colour=sig.cols, vjust=-1, hjust=1))
+        } else if (savePlot == FALSE && legend == FALSE){
+            p
         }
 
     },
diff --git a/R/plots.r b/R/plots.r
index b1e1499c95be4f4b94830b97220c82bf451dd0f4..5fb2f0e36307c18300159c50bd877ebf20a57e48 100644
--- a/R/plots.r
+++ b/R/plots.r
@@ -109,11 +109,6 @@ resumPlot2 = function(preparedData, contrCondi, savePlot = TRUE, directoryPath=
 
 }
 
-comparResumPlot2 = function(preparedData, savePlot = TRUE, directoryPath = directoryPath){
-  print("Plotting Summary comparison Plot for all conditions")
-  generateSummaryPlots(comparisonSummaryData(preparedData), savePlot = savePlot, file.name = paste(directoryPath, "_comparison_sumplot", sep = ""), format = "pdf")
-}
-
 cGSEAMakePlots = function(preparedData, directoryPath){
   dir.create(file.path(directoryPath,"/plots/"), showWarnings = FALSE)
   for (condi in names(preparedData$result)){
@@ -127,5 +122,5 @@ cGSEAMakePlots = function(preparedData, directoryPath){
     resumPlot2(preparedData = preparedData, contrCondi = condi, directoryPath = paste0(directoryPath,"/plots/",condi,"/"))
   }
   runTimePlot(preparedData = preparedData, directoryPath = paste0(directoryPath,"/plots/"))
-  comparResumPlot2(preparedData = preparedData, directoryPath = paste0(directoryPath,"/plots/"))
+  comparResumPlot(preparedData = preparedData, directoryPath = paste0(directoryPath,"/plots/"))
 }
diff --git a/R/setRankDBMaker.r b/R/setRankDBMaker.r
index 951f8e0eb4acd286340922261007a9dc6b399ecc..acdea8627a097648acccf621f9c4bd155ef3cf6a 100644
--- a/R/setRankDBMaker.r
+++ b/R/setRankDBMaker.r
@@ -1,68 +1,68 @@
-msig_to_setrankDb = function(msigdb, orga, dbname){
-  # msigdb : database R object
-  # orga : organism name (HUMAN|MOUSE)
-  # dbname : Msig database name (C2|H)
-  i = 1
-  df = data.frame(geneID = factor(), termID = factor(), termName = factor(), dbName = factor(), description = factor())
-  for (name in(names(msigdb))){
-    for (gene in msigdb[[name]]){
-      df = rbind(df, data.frame(geneID = factor(gene), termID = factor(paste(orga,"MSigDB",dbname,i,sep = "_")), termName = factor(name), dbName = factor("MSigDB"), description = factor("")))
-    }
-    i = i+1
-  }
-  return(df)
-}
-
-# #MOUSE
-load(url("http://bioinf.wehi.edu.au/software/MSigDB/mouse_H_v5p2.rdata"))
-load(url("http://bioinf.wehi.edu.au/software/MSigDB/mouse_c2_v5p2.rdata"))
+# msig_to_setrankDb = function(msigdb, orga, dbname){
+#   # msigdb : database R object
+#   # orga : organism name (HUMAN|MOUSE)
+#   # dbname : Msig database name (C2|H)
+#   i = 1
+#   df = data.frame(geneID = factor(), termID = factor(), termName = factor(), dbName = factor(), description = factor())
+#   for (name in(names(msigdb))){
+#     for (gene in msigdb[[name]]){
+#       df = rbind(df, data.frame(geneID = factor(gene), termID = factor(paste(orga,"MSigDB",dbname,i,sep = "_")), termName = factor(name), dbName = factor("MSigDB"), description = factor("")))
+#     }
+#     i = i+1
+#   }
+#   return(df)
+# }
 #
+# # #MOUSE
+# load(url("http://bioinf.wehi.edu.au/software/MSigDB/mouse_H_v5p2.rdata"))
+# load(url("http://bioinf.wehi.edu.au/software/MSigDB/mouse_c2_v5p2.rdata"))
+# #
+# #
+# # #HUMAN
+# load(url("http://bioinf.wehi.edu.au/software/MSigDB/human_H_v5p2.rdata"))
+# load(url("http://bioinf.wehi.edu.au/software/MSigDB/human_c2_v5p2.rdata"))
 #
-# #HUMAN
-load(url("http://bioinf.wehi.edu.au/software/MSigDB/human_H_v5p2.rdata"))
-load(url("http://bioinf.wehi.edu.au/software/MSigDB/human_c2_v5p2.rdata"))
-
-
-Mm.c2.kegg.subset = c(Mm.c2[grep("KEGG",attributes(Mm.c2)$names)])
-Mm.c2.reactome.subset = c(Mm.c2[grep("REACTOME", attributes(Mm.c2)$names)])
-
-Hs.c2.kegg.subset = c(Hs.c2[grep("KEGG",attributes(Hs.c2)$names)])
-Hs.c2.reactome.subset = c(Hs.c2[grep("REACTOME", attributes(Hs.c2)$names)])
-
-mouse_H = msig_to_setrankDb(Mm.H, "MOUSE", "H")
-mouse_C2_kegg = msig_to_setrankDb(Mm.c2.kegg.subset,"MOUSE","C2Kegg")
-mouse_C2_reactome = msig_to_setrankDb(Mm.c2.reactome.subset,"MOUSE","C2Reactome")
-
-
-
-human_H = msig_to_setrankDb(Hs.H,"HUMAN","H")
-human_C2_kegg = msig_to_setrankDb(Hs.c2.kegg.subset,"HUMAN","C2Kegg")
-human_C2_reactome = msig_to_setrankDb(Hs.c2.reactome.subset,"HUMAN","C2Reactome")
-
-MusCollectionH = buildSetCollection(mouse_H, referenceSet = allMusGenes, maxSetSize = 1450)
-MusCollectionC2Kegg = buildSetCollection(mouse_C2_kegg, referenceSet = allMusGenes, maxSetSize = 1450)
-MusCollectionC2Reactome = buildSetCollection(mouse_C2_reactome, referenceSet = allMusGenes, maxSetSize = 1450)
-
-HomoCollectionH = buildSetCollection(human_H, referenceSet = allHomoGenes, maxSetSize = 1450)
-HomoCollectionC2Kegg = buildSetCollection(human_C2_kegg, referenceSet = allHomoGenes, maxSetSize = 1450)
-HomoCollectionC2Reactome = buildSetCollection(human_C2_reactome, referenceSet = allHomoGenes, maxSetSize = 1450)
-
-
-save(MusCollectionH, file = "setRankMusCollection_H.RData")
-save(MusCollectionC2Kegg, file = "setRankMusCollection_C2Kegg.RData")
-save(MusCollectionC2Reactome, file = "setRankMusCollection_C2Reactome.RData")
-
-save(HomoCollectionH, file = "setRankHomoCollection_H.RData")
-save(HomoCollectionC2Kegg, file = "setRankHomoCollection_C2Kegg.RData")
-save(HomoCollectionC2Reactome, file = "setRankHomoCollection_C2Reactome.RData")
-
-# load("~/GitLab/DEA-DifferentialExpressionAnalysis/setRankHomoCollection_H.RData")
-# load("~/GitLab/DEA-DifferentialExpressionAnalysis/setRankHomoCollection_C2Kegg.RData")
-# load("~/GitLab/DEA-DifferentialExpressionAnalysis/setRankHomoCollection_C2Reactome.RData")
 #
-# load("~/GitLab/DEA-DifferentialExpressionAnalysis/setRankMusCollection_H.RData")
-# load("~/GitLab/DEA-DifferentialExpressionAnalysis/setRankMusCollection_C2Kegg.RData")
-# load("~/GitLab/DEA-DifferentialExpressionAnalysis/setRankMusCollection_C2Reactome.RData")
-
-# too slow when installin package - just put the .rdata files in the /data directory
-# devtools::use_data(MusCollectionH, MusCollectionC2Kegg, MusCollectionC2Reactome, HomoCollectionH, HomoCollectionC2Kegg, HomoCollectionC2Reactome, internal = TRUE, compress = "gzip", overwrite = TRUE)
+# Mm.c2.kegg.subset = c(Mm.c2[grep("KEGG",attributes(Mm.c2)$names)])
+# Mm.c2.reactome.subset = c(Mm.c2[grep("REACTOME", attributes(Mm.c2)$names)])
+#
+# Hs.c2.kegg.subset = c(Hs.c2[grep("KEGG",attributes(Hs.c2)$names)])
+# Hs.c2.reactome.subset = c(Hs.c2[grep("REACTOME", attributes(Hs.c2)$names)])
+#
+# mouse_H = msig_to_setrankDb(Mm.H, "MOUSE", "H")
+# mouse_C2_kegg = msig_to_setrankDb(Mm.c2.kegg.subset,"MOUSE","C2Kegg")
+# mouse_C2_reactome = msig_to_setrankDb(Mm.c2.reactome.subset,"MOUSE","C2Reactome")
+#
+#
+#
+# human_H = msig_to_setrankDb(Hs.H,"HUMAN","H")
+# human_C2_kegg = msig_to_setrankDb(Hs.c2.kegg.subset,"HUMAN","C2Kegg")
+# human_C2_reactome = msig_to_setrankDb(Hs.c2.reactome.subset,"HUMAN","C2Reactome")
+#
+# MusCollectionH = buildSetCollection(mouse_H, referenceSet = allMusGenes, maxSetSize = 1450)
+# MusCollectionC2Kegg = buildSetCollection(mouse_C2_kegg, referenceSet = allMusGenes, maxSetSize = 1450)
+# MusCollectionC2Reactome = buildSetCollection(mouse_C2_reactome, referenceSet = allMusGenes, maxSetSize = 1450)
+#
+# HomoCollectionH = buildSetCollection(human_H, referenceSet = allHomoGenes, maxSetSize = 1450)
+# HomoCollectionC2Kegg = buildSetCollection(human_C2_kegg, referenceSet = allHomoGenes, maxSetSize = 1450)
+# HomoCollectionC2Reactome = buildSetCollection(human_C2_reactome, referenceSet = allHomoGenes, maxSetSize = 1450)
+#
+#
+# save(MusCollectionH, file = "setRankMusCollection_H.RData")
+# save(MusCollectionC2Kegg, file = "setRankMusCollection_C2Kegg.RData")
+# save(MusCollectionC2Reactome, file = "setRankMusCollection_C2Reactome.RData")
+#
+# save(HomoCollectionH, file = "setRankHomoCollection_H.RData")
+# save(HomoCollectionC2Kegg, file = "setRankHomoCollection_C2Kegg.RData")
+# save(HomoCollectionC2Reactome, file = "setRankHomoCollection_C2Reactome.RData")
+#
+# # load("~/GitLab/DEA-DifferentialExpressionAnalysis/setRankHomoCollection_H.RData")
+# # load("~/GitLab/DEA-DifferentialExpressionAnalysis/setRankHomoCollection_C2Kegg.RData")
+# # load("~/GitLab/DEA-DifferentialExpressionAnalysis/setRankHomoCollection_C2Reactome.RData")
+# #
+# # load("~/GitLab/DEA-DifferentialExpressionAnalysis/setRankMusCollection_H.RData")
+# # load("~/GitLab/DEA-DifferentialExpressionAnalysis/setRankMusCollection_C2Kegg.RData")
+# # load("~/GitLab/DEA-DifferentialExpressionAnalysis/setRankMusCollection_C2Reactome.RData")
+#
+# # too slow when installin package - just put the .rdata files in the /data directory
+# # devtools::use_data(MusCollectionH, MusCollectionC2Kegg, MusCollectionC2Reactome, HomoCollectionH, HomoCollectionC2Kegg, HomoCollectionC2Reactome, internal = TRUE, compress = "gzip", overwrite = TRUE)