Merge pull request #42 from hancockinformatics/devel

Merge Devel 0.99.802

Author: travis-m-blimkie

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: ABCindex
 Title: A Shiny app to calculate ABCI for checkerboard assays
-Version: 0.99.78
+Version: 0.99.802
 Authors@R:
   person(given = "Travis",
          family = "Blimkie",

NEWS.md

@@ -0,0 +1,8 @@
+# ABCindex v0.99.802
+
+## Changes
+
+* Updated renv and package versions (a70c9b8)
+* Biomass reduction calculation was changed to prevent data from being inappropriately rescaled (ea922f2)
+* Changed sort order for concentrations in summary; Fixed message type for notify function (5a0611e)
+* Fixed typos in Help pages (387e574)

R/2_upload.R

@@ -133,7 +133,7 @@ abci_analysis_single <- function(
     )
 
   if (!normalize) {
-    if (max(data_clean[[col.data]]) >= 50) {
+    if (max(data_clean[[col.data]]) - min(data_clean[[col.data]]) > 10) {
       data_clean[[col.data]] <- data_clean[[col.data]] / 100
     }
   }
@@ -370,13 +370,13 @@ fill_card <- function(expt) {
     p(strong("Treatment in the columns: "), expt$cols$name),
     p(
       tags$b("Detected concentrations: "),
-      paste(sort(expt$cols$conc, decreasing = TRUE), collapse = ", ")
+      paste(sort(expt$cols$conc, decreasing = FALSE), collapse = ", ")
     ),
     hr(),
     p(strong("Treatment in the rows: "), expt$rows$name),
     p(
       strong("Detected concentrations: "),
-      paste(sort(expt$rows$conc, decreasing = TRUE), collapse = ", ")
+      paste(sort(expt$rows$conc, decreasing = FALSE), collapse = ", ")
     ),
   )
 }
@@ -418,7 +418,7 @@ notify <- function(id = NULL, list) {
   showNotification(
     id = id,
     type = list$type,
-    duration = ifelse(list$type == "success", 10, 20),
+    duration = ifelse(list$type == "message", 5, 20),
     ui = HTML(paste0(
       "<h4 class='alert-heading'><b>", list$status, "</b></h4>",
       "<p class='mb-0'>",
@@ -878,15 +878,13 @@ server_upload <- function(id) {
             "name" = unique(experiment$cols),
             "concentrations" = levels(experiment$cols_conc) %>%
               as.character() %>%
-              as.numeric() %>%
-              sort()
+              as.numeric()
           ),
           "rows" = list(
             "name" = unique(experiment$rows),
             "concentrations" = levels(experiment$rows_conc) %>%
               as.character() %>%
-              as.numeric() %>%
-              sort()
+              as.numeric()
           )
         )
       })

R/3_results.R

@@ -544,12 +544,14 @@ plot_dot <- function(
 
   # Fix up the variable being mapped to size. Define labels and breaks.
   data <- data %>%
-    group_by(.data[[col.analysis]]) %>%
     mutate(
       across(all_of(c(x.drug, y.drug)), forcats::fct_inseq),
-      reference = ceiling(scales::rescale(.data[[col.size]], to = c(0, 100)))
+      reference = ifelse(
+        test = ceiling(.data[[col.size]] * 100) <= 100,
+        yes = ceiling(.data[[col.size]] * 100),
+        no = 100
+      )
     ) %>%
-    ungroup() %>%
     left_join(size_mapping, by = "reference")
 
   proper_labels <- seq(0, 100, 20)
@@ -830,12 +832,14 @@ plot_dot_split <- function(
 
   # Fix up the variable being mapped to size. Define labels and breaks.
   data <- data %>%
-    group_by(.data[[col.analysis]]) %>%
     mutate(
       across(all_of(c(x.drug, y.drug)), forcats::fct_inseq),
-      reference = ceiling(scales::rescale(.data[[col.size]], to = c(0, 100)))
+      reference = ifelse(
+        test = ceiling(.data[[col.size]] * 100) <= 100,
+        yes = ceiling(.data[[col.size]] * 100),
+        no = 100
+      )
     ) %>%
-    ungroup() %>%
     left_join(size_mapping, by = "reference")
 
   proper_labels <- seq(0, 100, 20)
@@ -849,13 +853,11 @@ plot_dot_split <- function(
   if (!large.effect) {
     data <- mutate(data, large_chr = rep(0))
   } else {
-    data <- data %>%
-      mutate(
-        large_chr = ifelse(
-          (effect_avg > large.effect.val & data[[col.fill]] > abci.val),
-          yes = 1,
-          no = 0)
-      )
+    data <- mutate(data, large_chr = ifelse(
+      test = (effect_avg > large.effect.val & data[[col.fill]] > abci.val),
+      yes = 1,
+      no = 0
+    ))
   }
 
   # MICs are calculated by `get_mic()` and converted to positions on the axes
@@ -976,9 +978,9 @@ plot_dot_split <- function(
       x,
       col_size = scales::rescale(N1S2, to = size.range),
       col_size = ifelse(
-        !is.na(col_fill),
-        col_size,
-        0
+        test = !is.na(col_fill),
+        yes = col_size,
+        no = 0
       )
     )
   })