update network plot

R/MetAlyzer_handler.R

@@ -408,7 +408,7 @@ filterMetabolites <- function(metalyzer_se,
   }
 
   # Get all metabolites with at least one concentration being NA
-  if (!is.null(drop_NA_concentration)) {
+  if (drop_NA_concentration) {
     conc_values <- SummarizedExperiment::assay(
       metalyzer_se, "conc_values"
     )

R/calculate_anova.R

@@ -82,7 +82,7 @@ calculate_anova <- function(metalyzer_se, categorical, groups = NULL, impute_per
     mutate(ANOVA_n = sum(!is.na(.data$log2_Conc)))
 
   anova_data <- aggregated_data %>%
-    rename(Categorical = all_of(categorical)) %>%
+    dplyr::rename(Categorical = all_of(categorical)) %>%
     ungroup(.data$Categorical)
   cat(paste0("Info: Calculating ANOVA (groupwise: ",
              paste(groups(anova_data), collapse = " * "), ")...  "))

R/plot_log2FC.R

@@ -188,6 +188,9 @@ plot_log2FC <- function(metalyzer_se,
       select(.data$x) %>%
       max()
 
+    # Create y-axis limits for the rectangles
+    ylims <- c(min(log2FC_df$log2FC) - 0.75, max(log2FC_df$log2FC) + 0,75)
+
     ## Plot graph
     p_fc <- ggplot(p_data,
                    aes(x = .data$x,
@@ -197,7 +200,7 @@ plot_log2FC <- function(metalyzer_se,
       geom_rect(data = rects_df,
                 inherit.aes = FALSE,
                 aes(xmin = .data$Start, xmax = .data$End,
-                    ymin = -Inf, ymax = Inf,
+                    ymin = ylims[1], ymax = ylims[2],
                     fill = .data$Class),
                 show.legend = TRUE,
                 alpha = 0.4) +

R/plot_network.R

@@ -146,8 +146,8 @@ plot_network <- function(metalyzer_se, q_value=0.05) {
 
   # Create a plot of the network using ggplot2 and ggrepel
   label_size <- 3
-  area_size <- 5
-  edge_size <- 1
+  area_size <- 4
+  edge_size <- 0.75
   annotation_size <- 6
 
   network <- ggplot()
@@ -199,6 +199,8 @@ plot_network <- function(metalyzer_se, q_value=0.05) {
       size = label_size,
       color = "white"
     ) +
+    scale_fill_gradient2(low = "green", high = "magenta", mid = "black") +
+
     # Add annotations
     geom_text(
       data = pathways,
@@ -216,7 +218,7 @@ plot_network <- function(metalyzer_se, q_value=0.05) {
     # ylim(0, 10) +
     theme_void() +
     # Add a title and remove the x and y axis labels
-    ggtitle("Example Network Plot with Colored Area Behind Curved Edges") +
+    ggtitle("") +
     theme(plot.title = element_text(hjust = 0.5))
   network
 

inst/extdata/polarity.csv

@@ -22,12 +22,12 @@
 "21","Sugars","FIA"
 "22","Triacylglycerols","FIA"
 "23","Vitamins & Cofactors","LC"
-"24","Monoacylglycerols","LC"
-"25","Phosphatidic Acids","LC"
-"26","Phosphatidylcholines","LC"
-"27","Phosphatidylethanolamines","LC"
-"28","Phosphatidylglycerols","LC"
-"29","Phosphatidylinositols","LC"
-"30","Phosphatidylserines","LC"
-"31","Sphingoid Bases","LC"
-"32","Sphingomyelins","LC"
+"24","Monoacylglycerols","FIA"
+"25","Phosphatidic Acids","FIA"
+"26","Phosphatidylcholines","FIA"
+"27","Phosphatidylethanolamines","FIA"
+"28","Phosphatidylglycerols","FIA"
+"29","Phosphatidylinositols","FIA"
+"30","Phosphatidylserines","FIA"
+"31","Sphingoid Bases","FIA"
+"32","Sphingomyelins","FIA"

vignettes/MetAlyzer_User_Guide.Rmd

@@ -189,7 +189,7 @@ metalyzer_se <- calculate_anova(
   categorical = "Extraction_Method",
   groups = c("Tissue", "Metabolite"),
   impute_perc_of_min = 0.2,
-  impute_NA = FALSE
+  impute_NA = TRUE
 )
 
 aggregated_data <- aggregatedData(metalyzer_se) %>%