fix: add conflict management

comets_shinyapp_example/app.R

@@ -5,22 +5,40 @@ library(data.table)
 library(ggplot2)
 library(tidyverse)
 
+# Use conflicted to set preferences for conflicting functions
+conflict_prefer("between", "data.table")
+conflict_prefer("filter", "dplyr")
+conflict_prefer("first", "dplyr")
+conflict_prefer("hour", "lubridate")
+conflict_prefer("isoweek", "lubridate")
+conflict_prefer("lag", "dplyr")
+conflict_prefer("last", "dplyr")
+conflict_prefer("mday", "lubridate")
+conflict_prefer("minute", "lubridate")
+conflict_prefer("month", "lubridate")
+conflict_prefer("quarter", "lubridate")
+conflict_prefer("second", "lubridate")
+conflict_prefer("transpose", "purrr")
+conflict_prefer("wday", "lubridate")
+conflict_prefer("week", "lubridate")
+conflict_prefer("yday", "lubridate")
+conflict_prefer("year", "lubridate")
 
-abundance_df = fread("./species_abundance_filt.csv", 
-                            nThread = 8, drop = 1, header = T) %>% 
+abundance_df = fread("./species_abundance_filt.csv",
+                            nThread = 8, drop = 1, header = T) %>%
     rename("temperature"="soilTemp","pH" = "soilInCaClpH", "abundance"="percentage")
 
 # Read in data file for species selections - info on environmental preferences
-organism_df_to_subset = fread("./organism_data_to_subset.csv", drop = 1, header = T) %>% 
-    mutate(taxon=`Species of interest`) %>% 
+organism_df_to_subset = fread("./organism_data_to_subset.csv", drop = 1, header = T) %>%
+    mutate(taxon=`Species of interest`) %>%
     rename("Genome source" = source)
 
 # Read in data file to just show species names/links
 set.seed(1)
 organism_df_to_print = fread("./organism_data_to_print.csv", drop = 1, header = T)
 
 # Read in biome data file
-biome_info = fread("./nlcd_key.csv", drop = 1, header = T) 
+biome_info = fread("./nlcd_key.csv", drop = 1, header = T)
 biome_choices = biome_info$nlcdClass
 names(biome_choices) = biome_info$prettyNlcd
 
@@ -32,32 +50,32 @@ library(shinyhelper) # For adding help tooltips
 # UI
 ui <- fluidPage(
     titlePanel("SoilMicrobeDB: An Interactive Database of Soil Microbial Genomes"),
-    
+
     tags$p("The SoilMicrobeDB is a collection of over 30,000 soil microbial genomes, each annotated with ecological preferences for environmental conditions such as pH, temperature, and biome type. This tool allows you to filter, analyze, and visualize data on microbial species across different soil environments, using the sample collection from the National Ecological Observatory Network (NEON)."),
-    
+
     tags$h4("Filters"),
     fluidRow(
-        column(4, 
+        column(4,
                selectInput("biome", "Select Biome", choices = unique(organism_df_to_subset$biome), multiple = TRUE) %>%
                    shinyhelper::helper(
-                       type = "inline", 
-                       title = "Biome Preference", 
+                       type = "inline",
+                       title = "Biome Preference",
                        content = "Biome preference is assigned if a taxon is present in at least 2% of samples within the biome. Biomes are assigned to each NEON sample using the National Land Cover Database.",
                        icon = "question-circle"
                    )
-               
-               
+
+
         ),
-        column(4, 
-               sliderInput("pH_range", "pH Preference Range", min = 3, max = 9, value = c(3, 9)) %>% 
+        column(4,
+               sliderInput("pH_range", "pH Preference Range", min = 3, max = 9, value = c(3, 9)) %>%
                    shinyhelper::helper(
                        type = "inline",
                        title = "pH Preference",
                        content = "pH preference of each taxon is assigned as the peak of a LOESS curve fit to abundance data across the range of pH values. Click on a taxon to visualize or download this data.",
                        icon = "question-circle"
                    )
         ),
-        column(4, 
+        column(4,
                sliderInput("temperature_range", "Temperature Preference Range", min = 0, max = 40, value = c(0, 40)) %>%
                    shinyhelper::helper(
                        type = "inline",
@@ -67,20 +85,20 @@ ui <- fluidPage(
                    )
         )
     ),
-    
+
     tags$h4("Organism Data Table"),
     DT::dataTableOutput("organism_table"),
     downloadButton("download_organism", "Download Taxon List"),
-    
+
     uiOutput("modal_abundance_plot")
 )
 
 # Server
 server <- function(input, output, session) {
-    
+
     # Initialize shinyhelper
     shinyhelper::observe_helpers(withMathJax = TRUE)
-    
+
     # Reactive Filtered Organism DataFrame
     filtered_organism_df <- reactive({
         organism_df_to_subset %>%
@@ -90,28 +108,28 @@ server <- function(input, output, session) {
                 between(temperature_preference, input$temperature_range[1], input$temperature_range[2])
             )
     })
-    
+
     # Display Organism Data Table
     output$organism_table <- DT::renderDataTable({
         filtered_organism_df() %>% select(Kingdom, Genus, "Species of interest", "Genome source", "Functional in COMETS?")
     }, selection = 'single')
-    
+
     # Download Filtered Organism Data
     output$download_organism <- downloadHandler(
         filename = function() { paste("filtered_organism_data.csv") },
         content = function(file) { write.csv(filtered_organism_df(), file, row.names = FALSE) }
     )
-    
+
     # Modal Abundance Plot
     output$modal_abundance_plot <- renderUI({
         req(input$organism_table_rows_selected)
         selected_row <- filtered_organism_df()[input$organism_table_rows_selected, ]
         selected_taxon <- selected_row$taxon
-        
+
         # Filter abundance_df for selected taxon and check for data
         abundance_filtered <- abundance_df %>%
             filter(taxon == selected_taxon)
-        
+
         if (nrow(abundance_filtered) == 0) {
             # Show error message if no data is available for the selected taxon
             modalDialog(
@@ -135,68 +153,68 @@ server <- function(input, output, session) {
             )
         }
     })
-    
+
     # pH Plot
     output$pH_plot <- renderPlot({
         req(input$organism_table_rows_selected)
         selected_taxon <- filtered_organism_df()[input$organism_table_rows_selected, "taxon"]
         abundance_data <- abundance_df %>% filter(taxon == selected_taxon)
-        
+
         if (nrow(abundance_data) == 0) {
             return(NULL) # Avoid rendering if no data
         }
-        
-        ggplot(abundance_data, 
+
+        ggplot(abundance_data,
                aes(x = pH, y = abundance)) +#, color=nlcdClass)) +
             geom_point(aes(color=biome),
-                       alpha=.5, 
-                       position=position_jitter(width = .01, height=0), size=2) + 
+                       alpha=.5,
+                       position=position_jitter(width = .01, height=0), size=2) +
             #geom_smooth(method = "loess",show.legend = F, span=.7) +
             geom_smooth(method="gam",,
                         #method = "loess",
                         show.legend = F, se=F) +
-            theme_bw(base_size = 18) + 
-            #scale_y_sqrt() + 
-            xlab("Soil pH") + 
+            theme_bw(base_size = 18) +
+            #scale_y_sqrt() +
+            xlab("Soil pH") +
             labs(title = paste("Abundance vs. pH for", selected_taxon)) +
             ylab("Microbial abundance")
     })
-    
+
     # Temperature Plot
     output$temperature_plot <- renderPlot({
         req(input$organism_table_rows_selected)
         selected_taxon <- filtered_organism_df()[input$organism_table_rows_selected, "taxon"]
         abundance_data <- abundance_df %>% filter(taxon == selected_taxon)
-        
+
         if (nrow(abundance_data) == 0) {
             return(NULL) # Avoid rendering if no data
         }
-        
-        ggplot(abundance_data, 
+
+        ggplot(abundance_data,
                aes(x = temperature, y = abundance#, color=nlcdClass
                    )) +
             geom_point(aes(color=biome),
-                       alpha=.5, 
-                       position=position_jitter(width = .01, height=0), size=2) + 
+                       alpha=.5,
+                       position=position_jitter(width = .01, height=0), size=2) +
            # geom_smooth(method = "loess", show.legend = F, span=.7) +
             geom_smooth(method="gam",
-                #method = "loess", 
+                #method = "loess",
                 show.legend = F, se=F) +
-            theme_bw(base_size = 18) + 
-            #scale_y_sqrt()  + 
+            theme_bw(base_size = 18) +
+            #scale_y_sqrt()  +
             xlab("Soil temperature") +
             ylab("Microbial abundance") +
             labs(title = paste("Abundance vs. temperature for", selected_taxon))
-        
+
     })
-    
+
     # Download Filtered Abundance Data
     output$download_filtered_abundance <- downloadHandler(
         filename = function() { paste("taxon_abundance_data.csv") },
         content = function(file) {
             selected_taxon <- filtered_organism_df()[input$organism_table_rows_selected, "taxon"]
             abundance_data <- abundance_df %>% filter(taxon == selected_taxon)
-            
+
             if (nrow(abundance_data) > 0) {
                 write.csv(abundance_data, file, row.names = FALSE)
             }