final test for v1.5.1

Author: agusinac

CHANGELOG.md

@@ -3,6 +3,20 @@
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/)
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## v1.5.1 - [2026-02-27]
+
+### `Added`
+- Extended unit-tests to uncovered code sections.
+
+### `Changed`
+- Added error handling when none `SAMPLE_ID`s are matching during `private$sync`
+
+### `Fixed`
+- [#31](https://github.com/agusinac/OmicFlow/issues/31#issue-3962339783) `colormap` doesn't return any NAs.
+- [#30](https://github.com/agusinac/OmicFlow/issues/30#issue-3930823920) Placed `FEATURE_ID` as first column.
+- [#29](https://github.com/agusinac/OmicFlow/issues/29#issue-3930786231) replaced `position_nudge` with `position_jitter`
+- foldchange was matching sub-strings, fixed by changing it to exact matching.
+
 ## v1.5.0 - [2026-01-26]
 
 ### `Added`

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: OmicFlow
 Title: Fast and Efficient (Automated) Analysis of Sparse Omics Data
 Version: 1.5.1
-Date: 2026-02-23
+Date: 2026-02-27
 Authors@R: c(
     person(
         "Alem", "Gusinac",

R/foldchange.R

@@ -15,49 +15,35 @@
 #' #-------------------------#
 #' ##      NON-PAIRED       ##
 #' #-------------------------#
-#' # Load required library
 #' library(data.table)
-#' 
+#'
 #' # Define parameters and variables
-#' sample_ids <- c("S1_A", "S2_A", "S3_A", "S4_B", "S5_B", "S6_B")
+#' sample_ids <- c("S1", "S2", "S3", "S4", "S5", "S6")
+#' groups <- c("A", "A", "B", "B", "C", "C")
 #' feature_ids <- c("Feature1", "Feature2", "Feature3")
-#' 
+#'
 #' # Simulated abundance matrix (features x samples)
 #' abundances <- matrix(
 #'   c(
-#'     # Feature1 (e.g. GenusA)
-#'     100, 120, 110,  55, 60, 65,
-#'     # Feature2 (e.g. GenusB)
-#'     50, 65, 60,    130, 120, 125,
-#'     # Feature3 (e.g. GenusC)
-#'     80, 85, 90,     80, 85, 90
+#'     100, 120, 110, 55, 60, 65,
+#'     50, 65, 60, 130, 120, 125,
+#'     80, 85, 90, 80, 85, 90
 #'   ),
 #'   nrow = 3, byrow = TRUE,
 #'   dimnames = list(feature_ids, sample_ids)
 #' )
-#' 
-#' # A wide table with columns as samples, rows as features
-#' # And an additional column as the feature_rank, a column for feature comparison.
-#' mock_data <- data.table(
-#'   Genus = feature_ids,  # feature_rank column (e.g. "Genus")
-#'   S1_A = abundances[ , 1],
-#'   S2_A = abundances[ , 2],
-#'   S3_A = abundances[ , 3],
-#'   S4_B = abundances[ , 4],
-#'   S5_B = abundances[ , 5],
-#'   S6_B = abundances[ , 6]
-#' )
-#' print(mock_data)
-#' 
-#' # It uses substring matching, and multiple conditions can be used
+#'
+#' # Convert to a data.table
+#' mock_data <- OmicFlow::matrix_to_dtable(abundances)
+#' mock_data$Genus <- feature_ids
+#'
+#' # It uses exact matching and multiple conditions are allowed.
 #' res <- foldchange(
 #'   data = mock_data,
 #'   feature_rank = "Genus",
-#'   condition_A = c("_A", "_B"),
-#'   condition_B = c("_B", "_A"),
-#' 
-#'   # This can also be a column wherein, conditions A and B are present
-#'   condition_labels = sample_ids, 
+#'   condition_A = c("A", "B"),
+#'   condition_B = c("B", "C"),
+#'   condition_labels = groups,
 #'   paired = FALSE
 #' )
 #' print(res)
@@ -67,35 +53,16 @@
 #' #---------------------#
 #' library(data.table)
 #' 
-#' # Define paired sample ids for 3 pairs:
-#' paired_ids <- paste0("Pair", 1:3)
-#' 
-#' # Features:
-#' feature_ids <- c("Feature1", "Feature2", "Feature3")
-#' 
-#' # Simulate abundances for each paired sample:
-#' # For each pair, we have two samples: condition A and condition B.
-#' # Make sure the length of condition A and condition B are the same!
-#' 
-#' # Construct the data.table with features as rows
-#' mock_data_paired <- data.table(
-#'   Genus = feature_ids,
-#'   Pair1_A = c(100, 50, 80),
-#'   Pair1_B = c(60, 130, 75),
-#'   Pair2_A = c(120, 65, 85),
-#'   Pair2_B = c(60, 120, 90),
-#'   Pair3_A = c(110, 60, 90),
-#'   Pair3_B = c(65, 125, 85) 
-#' )
+#' # In the paired case both conditions A and B must be of the same length!
+#' # We re-use the above mock_data and only change group labels
+#' groups <- c("A", "A", "B", "B", "A", "B")
 #' 
 #' res <- foldchange(
-#'   data = mock_data_paired,
+#'   data = mock_data,
 #'   feature_rank = "Genus",
-#'   condition_A = c("_A", "_B"),
-#'   condition_B = c("_B", "_A"),
-#' 
-#'   # This can also be a column wherein, conditions A and B are present
-#'   condition_labels = names(mock_data_paired)[-1], 
+#'   condition_A = c("A"),
+#'   condition_B = c("B"),
+#'   condition_labels = groups,
 #'   paired = TRUE
 #' )
 #' print(res)