Merge pull request #122 from Cristianetaniguti/main

Avoid HTML + export bgzipped

DESCRIPTION

@@ -66,7 +66,8 @@ Imports:
     Matrix,
     matrixcalc,
     markdown,
-    Rsamtools
+    Rsamtools,
+    methods
 Remotes:
     github::jendelman/GWASpoly,
     github::Breeding-Insight/BIGr,

NAMESPACE

@@ -84,6 +84,7 @@ importFrom(httr,GET)
 importFrom(httr,content)
 importFrom(httr,status_code)
 importFrom(matrixcalc,is.positive.definite)
+importFrom(methods,new)
 importFrom(plotly,add_markers)
 importFrom(plotly,ggplotly)
 importFrom(plotly,layout)

R/DosageCall_functions.R

@@ -8,14 +8,20 @@
 #' @param backcross.gen ToDo
 #' @param intercross.gen ToDo
 #' @param selfing.gen ToDo
+#' @param min_ind_read ToDo
+#' @param min_ind_maf ToDo
 #' @param contamRate ToDo
+#' @param tol ToDo
 #' @param session ToDo
 #'
 #' @import polyRAD
 #' @importFrom vcfR read.vcfR is.biallelic write.vcf
 #' @importFrom R.utils gunzip
 #'
-polyRAD_dosage_call <- function(vcf, ploidy, model, p1 = NULL, p2 = NULL, backcross.gen = 0, intercross.gen = 0, selfing.gen = 0, contamRate = 0.001, min_ind_read = 1, min_ind_maf = 0, tol = 1e-05, session) {
+polyRAD_dosage_call <- function(vcf, ploidy, model, p1 = NULL, p2 = NULL,
+                                backcross.gen = 0, intercross.gen = 0, selfing.gen = 0,
+                                contamRate = 0.001, min_ind_read = 1, min_ind_maf = 0,
+                                tol = 1e-05, session) {
 
   # Variables
   vcf_path <- vcf
@@ -28,36 +34,36 @@ polyRAD_dosage_call <- function(vcf, ploidy, model, p1 = NULL, p2 = NULL, backcr
   # Having some issues formatting the output when multiallelic SNPs is input, so excluding for now
   temp_vcf <- vcfR::read.vcfR(vcf_path, verbose = FALSE)
   temp_vcf <- temp_vcf[is.biallelic(temp_vcf),]
-  
+
   # Function to randomly assign non-matching bases for polyRAD
   assign_random_bases <- function(vcf) {
     # Get the number of rows in the VCF
     num_rows <- nrow(vcf@fix)
-    
+
     # Generate random bases for REF and ALT
     bases <- c("A", "C", "G", "T")
     ref_bases <- sample(bases, num_rows, replace = TRUE)
     alt_bases <- character(num_rows) # Initialize an empty character vector
-    
+
     # Ensure REF and ALT are different for each row
     for (i in 1:num_rows) {
       alt_bases[i] <- sample(bases[bases != ref_bases[i]], 1)
     }
-    
+
     # Assign the new bases to the vcf object
     vcf@fix[, "REF"] <- ref_bases
     vcf@fix[, "ALT"] <- alt_bases
-    
+
     return(vcf)
   }
-  
+
   #Editing REF and ALT fields randomly temporarily if blank or AB
   ref_base <- temp_vcf@fix[1, "REF"]
   alt_base <- temp_vcf@fix[1, "ALT"]
   if (is.na(ref_base) || is.na(alt_base) || alt_base == "B") {
   temp_vcf <- assign_random_bases(temp_vcf)
   }
-  
+
   # Adding filtered VCF as a temp object
   temp_vcf_path <- tempfile(fileext = ".vcf.gz")
   vcfR::write.vcf(temp_vcf, file = temp_vcf_path)

R/mod_DosageCall.R

@@ -159,10 +159,10 @@ mod_DosageCall_ui <- function(id){
           )
         ),
         column(width=4,
-          valueBoxOutput(ns("MADCsnps"), width=12),
-          box(title = "Status", width = 12, collapsible = TRUE, status = "info",
-            progressBar(id = ns("pb_madc"), value = 0, status = "info", display_pct = TRUE, striped = TRUE, title = " ")
-          )
+               valueBoxOutput(ns("MADCsnps"), width=12),
+               box(title = "Status", width = 12, collapsible = TRUE, status = "info",
+                   progressBar(id = ns("pb_madc"), value = 0, status = "info", display_pct = TRUE, striped = TRUE, title = " ")
+               )
         )
       )
     )
@@ -256,15 +256,15 @@ mod_DosageCall_server <- function(input, output, session, parent_session){
   output$MADCsnps <- renderValueBox({
     valueBox(snp_number(), "Markers in uploaded file", icon = icon("dna"), color = "info")
   })
-  
+
   #Default model choices
   advanced_options <- reactiveValues(
     contamRate = 0.001,
     min_ind_read = 1,
     min_ind_maf = 0,
     tol = 1e-05
   )
-  
+
   #UI popup window for input
   observeEvent(input$advanced_options, {
     showModal(modalDialog(
@@ -310,17 +310,17 @@ mod_DosageCall_server <- function(input, output, session, parent_session){
       )
     ))
   })
-  
-  
-  
+
+
+
   #Close popup window when user "saves options"
   observeEvent(input$save_advanced_options, {
     advanced_options$contamRate <- input$contamRate
     advanced_options$min_ind_read <- input$min_ind_read
     advanced_options$min_ind_maf <- input$min_ind_maf
     advanced_options$tol <- input$tol
     # Save other inputs as needed
-    
+
     removeModal()  # Close the modal after saving
   })
 
@@ -555,12 +555,7 @@ mod_DosageCall_server <- function(input, output, session, parent_session){
   output$download_updog_vcf <- downloadHandler(
     filename = function() {
       output_name <- gsub("\\.vcf$", "", input$output_name)
-      if (input$Rpackage == "Updog") {
-        paste0(output_name, ".vcf.gz")
-      }else {
-        paste0(output_name, ".vcf")
-      }
-
+      paste0(output_name, ".vcf.gz")
     },
     content = function(file) {
 
@@ -571,24 +566,19 @@ mod_DosageCall_server <- function(input, output, session, parent_session){
           multidog.object = updog_out(),
           output.file = temp,
           updog_version = packageVersion("updog"),
-          compress = TRUE
+          compress = FALSE
         )
 
-        # Move the file to the path specified by 'file'
-        file.copy(paste0(temp, ".vcf.gz"), file)
-
       } else {
         polyRAD2vcf(updog_out()$Genos,
                     model = input$polyRAD_model,
                     vcf_path = input$madc_file$datapath,
                     hindhe.obj = updog_out()$RADHindHe,
                     ploidy = input$ploidy,
                     output.file = temp
-                    )
-
-        # Move the file to the path specified by 'file'
-        file.copy(paste0(temp, ".vcf"), file)
+        )
       }
+      bgzip_compress(paste0(temp, ".vcf"), file)
 
       # Delete the temporary file
       unlink(temp)

R/mod_Filtering.R

@@ -161,15 +161,15 @@ mod_Filtering_server <- function(input, output, session, parent_session){
     format_fields = NULL
 
   )
-  
+
   # Function to choose user selected dataset
   current_hist_data <- reactive({
     req(input$vcf_type)
-    
+
     # Switch between 'pre-filtered' or 'filtered' data based on user choice
     if (input$vcf_type == "Pre-Filter VCF") {
       list(
-        snp_miss = filtering_files$raw_snp_miss_df, 
+        snp_miss = filtering_files$raw_snp_miss_df,
         sample_miss = filtering_files$raw_sample_miss_df,
         maf_data = filtering_files$raw_maf_df
       )
@@ -226,7 +226,7 @@ mod_Filtering_server <- function(input, output, session, parent_session){
     }
 
     req(input$filter_ploidy, input$filter_output_name,input$updog_rdata)
-    
+
     #Status
     updateProgressBar(session = session, id = "pb_filter", value = 10, title = "Processing VCF file")
 
@@ -289,9 +289,9 @@ mod_Filtering_server <- function(input, output, session, parent_session){
     starting_samples <- ncol(gt_matrix)
     filtering_files$raw_snp_miss_df <- rowMeans(is.na(gt_matrix)) #SNP missing values
     filtering_files$raw_sample_miss_df <- as.numeric(colMeans(is.na(gt_matrix))) #Sample missing values
-    
+
     rm(gt_matrix) #Remove gt matrix
-    
+
     # Filtered VCF
     vcf <- filterVCF(vcf.file = vcf,
                      ploidy=ploidy,
@@ -348,7 +348,7 @@ mod_Filtering_server <- function(input, output, session, parent_session){
         color = "info"
       )
     })
-    
+
     #User warning if samples were removed during filtering
     sample_removed <- starting_samples - final_samples
     if (sample_removed > 0) {
@@ -370,21 +370,21 @@ mod_Filtering_server <- function(input, output, session, parent_session){
 
     # Status
     updateProgressBar(session = session, id = "pb_filter", value = 100, title = "Finished!")
-    
+
 
     vcf
   })
-  
+
   #Update plots
   output$din_tabs <- renderUI({
-    
+
     if (input$run_filters == 0) {
       tabBox(width =12, collapsible = FALSE, status = "info",
              id = "updog_tab", height = "600px",
              tabPanel("Results", p("Upload VCF file to access results in this section."))
       )
     } else {
-    
+
       if (!is.null(filtering_files$format_fields) && filtering_files$format_fields == TRUE && input$vcf_type == "Pre-Filter VCF") {
         # Include "Bias Histogram", "OD Histogram", and "Prop_mis Histogram" for Pre-Filtered VCF
         tabBox(
@@ -426,12 +426,16 @@ mod_Filtering_server <- function(input, output, session, parent_session){
       temp_file <- tempfile(fileext = ".vcf.gz")
       write.vcf(vcf(), file = temp_file)
 
+      # Avoid exporting gziped instead of bgziped
+      gunzip(temp_file)
+      temp_file <- gsub(".gz", "", temp_file)
+
       # Check if the VCF file was created
       if (file.exists(temp_file)) {
         cat("VCF file created successfully.\n")
 
         # Move the file to the path specified by 'file'
-        file.copy(temp_file, file, overwrite = TRUE)
+        bgzip_compress(temp_file, file)
 
         # Delete the temporary file
         unlink(temp_file)
@@ -542,7 +546,7 @@ mod_Filtering_server <- function(input, output, session, parent_session){
           xlim = c(0,1),
           breaks = as.numeric(input$hist_bins))
         axis(1, at = seq(0, 1, by = .1), labels = rep("", length(seq(0, 1, by = 0.1))))  # Add ticks
-        
+
         # Add vertical lines
         abline(v = mean(as.numeric(current_hist_data()$snp_miss)), col = "red", lty = 2)  # Mean line
         abline(v = median(as.numeric(current_hist_data()$snp_miss)), col = "green", lty = 2)  # Median line
@@ -562,7 +566,7 @@ mod_Filtering_server <- function(input, output, session, parent_session){
           xlim = c(0,1),
           breaks = as.numeric(input$hist_bins))
         axis(1, at = seq(0, 1, by = .1), labels = rep("", length(seq(0, 1, by = 0.1))))  # Add ticks
-        
+
         # Add vertical lines
         abline(v = mean(as.numeric(current_hist_data()$sample_miss)), col = "red", lty = 2)  # Mean line
         abline(v = median(as.numeric(current_hist_data()$sample_miss)), col = "green", lty = 2)  # Median line
@@ -678,7 +682,7 @@ mod_Filtering_server <- function(input, output, session, parent_session){
     #Missing data
     output$missing_snp_hist <- renderPlot({
       req(current_hist_data()$snp_miss)
-      
+
       #Histogram
       hist(
         as.numeric(current_hist_data()$snp_miss),