adds rank ordering and a better dataset

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: ICIKendallTau
 Title: Calculates information-content-informed Kendall-tau
-Version: 1.1.0
+Version: 1.1.1
 Authors@R: c(
     person(
       given = c("Robert", "M"), 
@@ -40,5 +40,7 @@ Suggests: furrr,
           naniar
 URL: https://moseleybioinformaticslab.github.io/ICIKendallTau/
         https://github.com/moseleybioinformaticslab/ICIKendallTau/
-BugReports: https://github.com/moseleybioinformaticslab/ICIKendallTau/issues
+BugReports:
+        https://github.com/moseleybioinformaticslab/ICIKendallTau/issues
 Config/testthat/edition: 3
+Depends: R (>= 2.10)

R/left_censorship.R

@@ -156,3 +156,15 @@ add_uniform_noise = function(value, n_rep, sd, use_zero = FALSE){
 #' 
 #' @source Robert M Flight
 "missing_dataset"
+
+#' Example RNA-Seq Dataset With Missingness
+#' 
+#' An example dataset from RNA-seq experiment on yeast, created by Gierliński et al.,
+#' "Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment",
+#' Bioinformatics, 31, 2015 <https://doi.org/10.1093/bioinformatics/btv425>.
+#' 
+#' @format ## `yeast_missing`
+#' A matrix with 6887 rows (genes) and 96 columns (samples).
+#' 
+#' @source <https://dx.doi.org/10.6084/M9.FIGSHARE.1425502.V1> <https://dx.doi.org/10.6084/M9.FIGSHARE.1425503.V1>
+"yeast_missing"

R/rank-ordering.R

@@ -0,0 +1,19 @@
+rank_order_data = function(data_matrix, global_na = c(NA, Inf, 0))
+{
+  missing_loc = setup_missing_matrix(data_matrix, global_na)
+  data_matrix_na = data_matrix
+  data_matrix_na[missing_loc] = NA
+  sample_ranks = purrr::map(seq_len(ncol(data_matrix_na)), \(in_col){
+    rank(data_matrix_na[, in_col], na.last = FALSE)
+
+  })
+  sample_ranks = do.call(cbind, sample_ranks)
+  median_ranks = apply(sample_ranks, 1, median)
+  rank_order = order(median_ranks, decreasing = TRUE)
+
+  perc_missing = colSums(is.na(data_matrix_na)) / nrow(data_matrix_na)
+  perc_order = order(perc_missing, decreasing = TRUE)
+
+  return(original = data_matrix_na,
+         ordered = data_matrix_na[rank_order, perc_order])
+}