I added GOSemSim Output table

GOSemSim.R

@@ -3,11 +3,14 @@ library(org.Dm.eg.db)
 #Reference for Fly
 d = godata('org.Dm.eg.db', ont = "BP", computeIC = FALSE)
 contrast = read.csv("contrasts_mite_life_stages.csv", header = F)
-similarities_upregulated = c()
-similarities_downregulated = c()
+
+similarities_upregulated = list()
+similarities_downregulated = list()
+contrast_names = list()
 
 for (id in 1:length(contrast$V1))
 {
+  print(paste(id, "id"))
   first_contrast = toString(contrast$V1[id])
   second_contrast = toString(contrast$V2[id])
 
@@ -20,7 +23,9 @@ for (id in 1:length(contrast$V1))
   GO2 = read.csv(filename, header = T)
   GO2ID = as.character(GO2[,1])
 
-  similarities_upregulated[id] = mgoSim(GO1ID, GO2ID, semData = d, measure = "Wang", combine = "BMA")
+  name = paste(first_contrast, "_", second_contrast,sep = "")
+  contrast_names[length(contrast_names)+1] = name
+  similarities_upregulated[[length(similarities_upregulated)+1]] = mgoSim(GO1ID, GO2ID, semData = d, measure = "Wang", combine = "BMA")
 
   #DOWN-REGULATED
   filename = paste("./GO_enrichment_microbiome_output/contrast_", first_contrast, "_", second_contrast, "_downregulated", ".csv", sep = "")
@@ -31,5 +36,10 @@ for (id in 1:length(contrast$V1))
   GO2 = read.csv(filename, header = T)
   GO2ID = as.character(GO2[,1])
 
-  similarities_downregulated[id] = mgoSim(GO1ID, GO2ID, semData = d, measure = "Wang", combine = "BMA")
-}
+  similarities_downregulated[[length(similarities_downregulated)+1]] = mgoSim(GO1ID, GO2ID, semData = d, measure = "Wang", combine = "BMA")
+}
+
+names(similarities_downregulated) = as.vector(unlist(contrast_names))
+names(similarities_upregulated) = as.vector(unlist(contrast_names))
+GOSemSim_table = do.call(rbind, Map(data.frame, A=similarities_upregulated, B=similarities_downregulated))
+write.csv(GOSemSim_table, "GOSemSim_table.csv")

GOSemSim_table.csv

@@ -0,0 +1,13 @@
+,Up_regulated,Down_regulated
+young_males,0.763,0.917
+young_phoretic,0.803,0.887
+phoretic_phoreticCaged,0.798,0.866
+phoretic_arresting,0.759,0.901
+arresting_prelaying,0.793,0.892
+prelaying_laying,0.799,0.899
+laying_postlaying,0.782,0.911
+postlaying_emerging,0.817,0.864
+postlaying_nonlaying,0.811,0.884
+laying_nonlaying,0.8,0.899
+emerging_phoretic,0.785,0.891
+emerging_young,0.816,0.881