imputation information are now added to the final limma results

ms_workflow/ms_limma.R

@@ -163,6 +163,7 @@ expMatrix = countData %>%
 
 
 # remove rows with rowSums == 0
+# to remove non-zero rows slightly changes the results
 all_rows <- expMatrix %>% nrow()
 expMatrix <- expMatrix[rowSums(expMatrix) > 0, ]
 non_zero_rows <- expMatrix %>% nrow()
@@ -485,6 +486,26 @@ if(nrow(degs)>0){
 #'
 #'<br>
 #'
+imp_info <- file.path(ms_data_infos, "data_prep.imputation_info.txt")
+if (file.exists(ident_info)) {
+    imp <- read_tsv(imp_info)
+
+    # extract which condition is reported in the de_results
+    d <- gather(imp, feature, value, -intensity) %>% filter(value %in% unique(deAnnot$condition_1)) %$% feature %>% unique()
+
+    imp <- imp[,colnames(imp) %in% c("protein_ids", "is_imputed", d)] %>%
+    push_left(c("protein_ids", "is_imputed"))
+    colnames(imp)[3] <- "condition"
+
+    imp %<>% group_by(protein_ids, condition) %>%
+        count(is_imputed) %>%
+        select(-n)
+
+    deAnnot %<>%
+        left_join(imp %>% rename(c1_imp = is_imputed), by = c("protein_ids", "condition_1" = "condition")) %>%
+        left_join(imp %>% rename(c2_imp = is_imputed), by = c("protein_ids", "condition_2" = "condition"))
+}
+
 
 ########################################################################################################################
 #' ## Results & Discussion