chore: minor improvements

gdrplatform · Dec 16, 2024 · 94501bb · 94501bb
1 parent df6d275
commit 94501bb
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Showing 2 changed files with 16 additions and 4 deletions.
diff --git a/R/fit_curves.R b/R/fit_curves.R
@@ -78,7 +78,7 @@ fit_curves <- function(df_,
   if (length(setdiff(opt_fields, colnames(df_))) > 0L) {
     df_[, setdiff(opt_fields, colnames(df_))] <- NA
   }
-  df_metrics <- .apllyLogisticFit(df_, normalization_type, series_identifiers, e_0, GR_0, range_conc, force_fit, 
+  df_metrics <- .applyLogisticFit(df_, normalization_type, series_identifiers, e_0, GR_0, range_conc, force_fit, 
                                   pcutoff, cap, n_point_cutoff)
 
   is_unique_normalization_type_and_fit_source <- 
@@ -94,7 +94,7 @@ fit_curves <- function(df_,
 }
 
 #' @keywords internal
-.apllyLogisticFit <- function(df_, normalization_type, series_identifiers, e_0, GR_0, range_conc, force_fit, 
+.applyLogisticFit <- function(df_, normalization_type, series_identifiers, e_0, GR_0, range_conc, force_fit, 
                               pcutoff, cap, n_point_cutoff) {
 
   df_metrics <- NULL
@@ -487,7 +487,12 @@ logistic_metrics <- function(c, x_metrics) {
 #' @keywords fit_curves
 #' @export
 .setup_metric_output <- function() {
-  resp_metric_cols <- c(get_header("response_metrics"), "maxlog10Concentration", "N_conc")
+  resp_metric_all_cols <- c(get_header("response_metrics"), "maxlog10Concentration", "N_conc")
+  # remove cols ending with "_sd"
+  # they are not present in the primary assays 
+  # but only with the assays followed by averaging of biological replicates
+  resp_metric_cols <- grep("_sd$", resp_metric_all_cols, invert = TRUE, value = TRUE) 
+
   out <- as.list(rep(NA, length(resp_metric_cols)))
   names(out) <- resp_metric_cols
   out

diff --git a/R/flatten.R b/R/flatten.R
@@ -56,7 +56,14 @@ flatten <- function(tbl, groups, wide_cols, sep = "_") {
   uniquifying <- unique(uniquifying)
 
   out <- split(subset(tbl, select = -idx), subset(tbl, select = idx), sep = sep)
-  missing <- setdiff(wide_cols, colnames(tbl))
+
+  # in original assays there are no columns with SD-related data (with names ending with "_sd")
+  missing <- if (!any(grepl("_sd$", colnames(tbl)))) {
+    setdiff(wide_cols[!grepl("_sd$", wide_cols)], colnames(tbl))
+  # assays with averaged biological replicates might have columns with SD-related data (with names ending with "_sd")
+  } else {
+    setdiff(wide_cols, colnames(tbl))
+  }
   if (length(missing) != 0L) {
     warning(sprintf("missing listed wide_cols columns: '%s'", paste0(missing, collapse = ", ")))
   }