exclude failed samples from annotation report

R/modules/annot/prepare_summary.R

@@ -2,15 +2,14 @@ source(file.path(src_dir, "src/samnsero_summary.R"))
 if (exists("amr_res_clean")) amr_drug_summary <- amr_class_sum(amr_res_clean)
 if (!is_empty(annot_summary)) {
 	# create presence/absence matrix of each annotation type
-	tidy_res <- annot_sum2mat(annot_summary, var_only = F)
-	plasmid_summary <- getSummaryType(tidy_res, "Plasmid")
-	amr_summary <- getSummaryType(tidy_res, "AMR")
-	vf_summary <- getSummaryType(tidy_res, "Virulence Factor")
+	tidy_res <- annot_sum2mat(annot_summary, var_only = F) %>% select(sistr_res_clean$id)
+	plasmid_summary <- getSummaryType(tidy_res, "Plasmid") %>% select(sistr_res_clean$id)
+	amr_summary <- getSummaryType(tidy_res, "AMR") %>% select(sistr_res_clean$id)
+	vf_summary <- getSummaryType(tidy_res, "Virulence Factor") %>% select(sistr_res_clean$id)
 	# create presence/absence matrix of each annotation type (variable elements only)
-	tidy_res_var <- annot_sum2mat(annot_summary, var_only = T)
-	plasmid_summary_var <- getSummaryType(tidy_res_var, "Plasmid")
-	amr_summary_var <- getSummaryType(tidy_res_var, "AMR")
-	vf_summary_var <- getSummaryType(tidy_res_var, "Virulence Factor")
-
+	tidy_res_var <- annot_sum2mat(annot_summary, var_only = T) %>% select(sistr_res_clean$id)
+	plasmid_summary_var <- getSummaryType(tidy_res_var, "Plasmid") %>% select(sistr_res_clean$id)
+	amr_summary_var <- getSummaryType(tidy_res_var, "AMR") %>% select(sistr_res_clean$id)
+	vf_summary_var <- getSummaryType(tidy_res_var, "Virulence Factor") %>% select(sistr_res_clean$id)
 }
 

R/src/mob_suite_transpose.R

@@ -36,7 +36,7 @@ summary <- function(df) {
 			)
 		}) %>%
 		bind_rows() %>% 
-		#mutate(id = factor(id, levels = samples)) %>% 
+		mutate(id = factor(id, levels = samples)) %>% 
 		pivot_wider(names_from = id,
 								values_from = value,
 								values_fill = ".",

R/src/rgi_transpose.R

@@ -24,7 +24,7 @@ summary <- function(df) {
 		arrange(desc(Best_Identities)) %>% 
 		slice(1) %>% 
 		ungroup() %>% 
-		mutate(#id = factor(id, levels = samples),
+		mutate(id = factor(id, levels = samples),
 					 Best_Identities = as.character(Best_Identities)) %>% 
 		pivot_wider(names_from = "id",
 								values_from = "Best_Identities",

R/src/samnsero_summary.R

@@ -52,6 +52,7 @@ amr_class_sum <- function(df) {
 		pivot_wider(names_from = "id",
 								values_from = "n",
 								values_fill = 0,
+								values_fn = ~return(.[1]),
 								names_expand = T) %>% 
 		column_to_rownames("Drug Class")
 }