changed an argument name to be more standardized

R/sortObservations.R

@@ -5,7 +5,7 @@
 #' @importFrom dplyr arrange
 #' @description Since the GEE & GLMM modes require data to be sorted by sample ID and pseudotime, this function provides a simple way to do so for a range of inputs.
 #' @param expr.mat Either a \code{SingleCellExperiment} or \code{Seurat} object from which counts can be extracted, or a matrix of integer-valued counts with genes as rows & cells as columns. Defaults to NULL.
-#' @param pt A vector of pseudotime values used to sort the observations. May contain NA values. Defaults to NULL.
+#' @param pt.vec A vector of pseudotime values used to sort the observations. May contain NA values. Defaults to NULL.
 #' @param id.vec A vector of subject IDs used to sort the observations. Defaults to NULL.
 #' @return An object of the same class as the input \code{expr.mat}, but sorted by sample ID & pseudotime.
 #' @details
@@ -21,14 +21,14 @@
 #'                                   id.vec = sim_counts$subject)
 
 sortObservations <- function(expr.mat = NULL,
-                             pt = NULL,
+                             pt.vec = NULL,
                              id.vec = NULL) {
   # check inputs
   if (is.null(expr.mat) || is.null(pt) || is.null(id.vec)) { stop("You forgot some inputs to sortObservations().") }
   if (any(is.na(id.vec))) { stop("The subject ID vector must not contain any NA values.") }
   # create table with subject ID and pseudotime
   subj_df <- data.frame(ID = id.vec,
-                        PT = pt,
+                        PT = pt.vec,
                         Cell = colnames(expr.mat))
   # arrange by subject ID then pseudotime
   subj_df <- dplyr::arrange(subj_df,