Merge branch 'main' of https://github.com/nilsmechtel/MetAlyzer into …

…new_changes

.Rbuildignore

@@ -7,17 +7,10 @@
 ^\.\.Rcheck.*
 ^LICENSE$
 ^cran-comments\.md$
+.*_cache$
 
 ^tests/.*
 
-^vignettes/.*
-
-^R/calculate_anova\.R$
-^R/calculate_cv\.R$
-
-^R/add_filter\.R$
 ^R/do_anova_2w\.R$
-^R/filter_groupwise\.R$
-^R/perform_anova\.R$
 ^R/plot_2w_anvova\.R$
-^R/two_way_anova\.R$
+^R/two_way_anova\.R$

.gitignore

@@ -6,3 +6,4 @@
 *.code-workspace
 .Rproj.user
 ..Rcheck
+*_cache

DESCRIPTION

@@ -23,21 +23,23 @@ Authors@R:
             comment = c(ORCID = "0000-0002-6041-7049")))
 Depends:
     R (>= 4.0.0)
+biocViews:
 Imports:
+    SummarizedExperiment,
     openxlsx,
+    stringr,
     dplyr,
     tidyr,
-    stringr,
-    utils,
-    rlang,
+    tibble,
+    agricolae,
     ggplot2,
     ggrepel,
-    SummarizedExperiment,
-    S4Vectors,
-    BiocManager,
-    qvalue,
+    utils,
+    rlang,
     methods,
-    data.table
+    data.table,
+    S4Vectors,
+    qvalue
 Description: The 'MetAlyzer' S4 object provides methods to read and reformat metabolomics data for convenient data handling, statistics and downstream analysis. The resulting format corresponds to input data of the Shiny app 'MetaboExtract' (<https://www.metaboextract.shiny.dkfz.de/MetaboExtract/>).
 License: GPL-3
 Encoding: UTF-8

NAMESPACE

@@ -2,14 +2,16 @@
 
 export(MetAlyzer_dataset)
 export(aggregatedData)
+export(calculate_anova)
+export(calculate_cv)
 export(calculate_log2FC)
 export(example_extraction_data)
 export(example_meta_data)
 export(example_mutation_data_xl)
-export(example_treatment_data)
 export(exportConcValues)
 export(filterMetaData)
 export(filterMetabolites)
+export(log2FC)
 export(metalyzer_colors)
 export(pathway)
 export(plot_log2FC)
@@ -24,8 +26,8 @@ import(dplyr)
 import(ggplot2)
 import(ggrepel)
 importFrom(data.table,":=")
-importFrom(methods,is)
 importFrom(rlang,.data)
+importFrom(stats,aov)
 importFrom(stats,lm)
-importFrom(utils,install.packages)
-importFrom(utils,installed.packages)
+importFrom(tibble,deframe)
+importFrom(tibble,rownames_to_column)

R/MetAlyzer_dataset.R

@@ -101,9 +101,9 @@ MetAlyzer_dataset <- function(
   return(se)
 }
 
-#' MetAlyzer logo
+#' @title MetAlyzer logo
 #'
-#' This function prints "MetAlyzer" as an ASCII logo
+#' @description This function prints "MetAlyzer" as an ASCII logo
 #'
 #' @keywords internal
 metalyzer_ascii_logo <- function() {
@@ -144,9 +144,9 @@ metalyzer_ascii_logo <- function() {
 }
 
 
-#' Open Excel file
+#' @title Open Excel file
 #'
-#' This function opens the given MetIDQ output Excel file and reads the full
+#' @description This function opens the given MetIDQ output Excel file and reads the full
 #' given sheet.
 #'
 #' @param starter_list contains the file path and the sheet index
@@ -165,9 +165,9 @@ open_file <- function(starter_list) {
 }
 
 
-#' Get data range
+#' @title Get data range
 #'
-#' This function extracts rows and column indices to slice the .full_sheet into
+#' @description This function extracts rows and column indices to slice the .full_sheet into
 #' metabolites, conc_values and meta_data.
 #'
 #' @param full_sheet full_sheet
@@ -208,10 +208,10 @@ get_data_range <- function(full_sheet) {
 }
 
 
-#' Slice metabolites
+#' @title Slice metabolites
 #'
-#' This function extracts metabolites with their corresponding metabolite class
-#' from .full_sheet into metabolites.
+#' @description This function extracts metabolites with their corresponding
+#' metabolite class from .full_sheet into metabolites.
 #'
 #' @param full_sheet full_sheet
 #' @param data_ranges data_ranges
@@ -232,9 +232,10 @@ slice_metabolites <- function(full_sheet, data_ranges) {
 }
 
 
-#' Slice concentration values
+#' @title Slice concentration values
 #'
-#' This function slices measurements from .full_sheet into conc_values.
+#' @description This function slices measurements from .full_sheet into
+#' conc_values.
 #'
 #' @param full_sheet full_sheet
 #' @param data_ranges data_ranges
@@ -253,9 +254,9 @@ slice_conc_values <- function(full_sheet, data_ranges, metabolites) {
 }
 
 
-#' Slice meta data
+#' @title Slice meta data
 #'
-#' This function slices meta data from .full_sheet into meta_data.
+#' @description This function slices meta data from .full_sheet into meta_data.
 #'
 #' @param full_sheet full_sheet
 #' @param data_ranges data_ranges
@@ -282,10 +283,10 @@ slice_meta_data <- function(full_sheet, data_ranges) {
 }
 
 
-#' Unify hex codes
+#' @title Unify hex codes
 #'
-#' This function gets hex codes of different length and returns them in a
-#' unified format.
+#' @description This function gets hex codes of different length and returns
+#' them in a unified format.
 #'
 #' @param hex A 3, 4, 6 or 8 digit hex code
 #'
@@ -317,10 +318,10 @@ unify_hex <- function(hex) {
 }
 
 
-#' Read quantification status
+#' @title Read quantification status
 #'
-#' This function gets the background color of each cell in .full_sheet and
-#' assigns it to the corresponding quantification status.
+#' @description This function gets the background color of each cell in 
+#' full_sheet and assigns it to the corresponding quantification status.
 #'
 #' @param starter_list starter_list
 #' @param sheet_dim sheet_dim
@@ -378,9 +379,9 @@ read_quant_status <- function(
   return(quant_status)
 }
 
-#' Aggregate data
+#' @title Aggregate data
 #'
-#' This function reshapes conc_values, quant_status,
+#' @description This function reshapes conc_values, quant_status,
 #' metatabolites and sample IDs and combines them into a tibble data frame
 #' for filtering with dplyr and plotting with 'ggplot2'. "aggregated_data"
 #' is grouped by metabolites.

R/MetAlyzer_fpaths.R

@@ -12,20 +12,6 @@ example_extraction_data <- function() {
 }
 
 
-#' @title Get example treatment data
-#'
-#' @description This function returns the treatment_data_MxP_Quant_500.xlsx file path.
-#'
-#' @return treatment_data_MxP_Quant_500.xlsx file path
-#' @export
-#'
-#' @examples
-#' fpath <- example_treatment_data()
-example_treatment_data <- function() {
-  system.file("extdata", "treatment_data_MxP_Quant_500.xlsx", package = "MetAlyzer")
-}
-
-
 #' @title Get example mutation data
 #'
 #' @description This function returns the mutation_data_MxP_Quant_500_XL.xlsx file path.

R/MetAlyzer_handler.R

@@ -127,11 +127,11 @@ filterMetaData <- function(metalyzer_se, ..., inplace = FALSE) {
   # Print how many samples were removed
   diff <- nrow(meta_data) - length(true_samples)
   if (diff == 1) {
-    cat("1 sample was removed!\n")
+    cat("Info: 1 sample was removed!\n")
   } else if (diff > 1) {
-    cat(paste(diff, "samples were removed!\n"))
+    cat("Info:", paste(diff, "samples were removed!\n"))
   } else {
-    cat("No samples were removed!\n")
+    cat("Info: No samples were removed!\n")
   }
 
   if (inplace) {
@@ -369,7 +369,7 @@ filterMetabolites <- function(metalyzer_se,
         )
       }
       cat(
-        "A group counts as valid, if at least ",
+        "Info: A group counts as valid, if at least ",
         round(min_percent_valid * 100, 2),
         "% of samples are considered as valid.\n",
         "Group-wise calculation: (",
@@ -379,7 +379,7 @@ filterMetabolites <- function(metalyzer_se,
       )
     } else {
       cat(
-        "A metabolite counts as valid, if at least ",
+        "Info: A metabolite counts as valid, if at least ",
         round(min_percent_valid * 100, 2),
         "% of samples are considered as valid.\n",
         sep = ""
@@ -438,11 +438,11 @@ filterMetabolites <- function(metalyzer_se,
 
   diff <- length(rm_metabolites)
   if (diff == 1) {
-    cat("1 metabolite was removed!\n")
+    cat("Info: 1 metabolite was removed!\n")
   } else if (diff > 1) {
-    cat(paste(diff, "metabolites were removed!\n"))
+    cat("Info:", paste(diff, "metabolites were removed!\n"))
   } else {
-    cat("No metabolites were removed!\n")
+    cat("Info: No metabolites were removed!\n")
   }
 
   if (inplace) {
@@ -456,7 +456,7 @@ filterMetabolites <- function(metalyzer_se,
 # === Handle Aggregated Data ===
 #' @title Get Aggregated Data
 #'
-#' @description This function returns the tibble data frame "aggregated_data".
+#' @description This function returns the tibble "aggregated_data".
 #'
 #' @param metalyzer_se SummarizedExperiment
 #' @export
@@ -469,6 +469,37 @@ aggregatedData <- function(metalyzer_se) {
   return(metalyzer_se@metadata$aggregated_data)
 }
 
+# === Handle log2FC Data ===
+#' @title Get log2FC Data
+#'
+#' @description This function returns the tibble "log2FC".
+#'
+#' @param metalyzer_se SummarizedExperiment
+#' @export
+#'
+#' @examples
+#' metalyzer_se <- MetAlyzer_dataset(file_path = example_mutation_data_xl())
+#' metalyzer_se <- filterMetabolites(
+#'   metalyzer_se,
+#'   drop_metabolites = "Metabolism Indicators"
+#' )
+#' metalyzer_se <- renameMetaData(
+#'   metalyzer_se,
+#'   Mutant_Control = "Sample Description"
+#' )
+#' 
+#' metalyzer_se <- calculate_log2FC(
+#'   metalyzer_se,
+#'   categorical = "Mutant_Control",
+#'   impute_perc_of_min = 0.2,
+#'   impute_NA = TRUE
+#' )
+#'
+#' log2FC(metalyzer_se)
+log2FC <- function(metalyzer_se) {
+  return(metalyzer_se@metadata$log2FC)
+}
+
 # === Export data ===
 
 #' @title Export filtered raw data as csv
@@ -497,8 +528,8 @@ exportConcValues <- function(metalyzer_se,
     dplyr::select(meta_data, ...),
     t(conc_values)
   )
-  cat("Number of samples:", nrow(meta_data), "\n")
-  cat("Number of Metabolites:", nrow(conc_values), "\n")
+  cat("Info: Number of samples:", nrow(meta_data), "\n")
+  cat("Info: Number of Metabolites:", nrow(conc_values), "\n")
   utils::write.csv(
     x = df,
     file = file_path,