corrections of typos before pushing to CRAN

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: banffIT
 Type: Package
-Title: Automatize Standardized Assignation Diagnosis Using the Banff Classification 
+Title: Automatize Diagnosis Standardized Assignation Using the Banff Classification
 Version: 0.1.0
 Authors@R: 
     c(person(given = "Guillaume",
@@ -19,16 +19,20 @@ Authors@R:
       person(given = "Jérôme",
              family = "Laforme",
              role=c("ctb"),
-             email="jlaforme@maelstrom-research.org"))
+             email="jlaforme@maelstrom-research.org"),
+      person(given = "Tina",
+             family = "Wey",
+             role=c("ctb"),
+             email="twey@maelstrom-research.org"))
 Maintainer: Guillaume Fabre <guijoseph.fabre@gmail.com>
 Description: The goal of this package is to provide functions to assign 
-    standardized diagnosis using the Banff Classification (Category 1 to 6 
+    standardized diagnoses using the Banff Classification (Category 1 to 6 
     diagnoses, including Acute and Chronic active T-cell mediated rejection as 
     well as Active, Chronic active, and Chronic antibody mediated rejection). 
-    The main function considers a minimal dataset containing biopsy 
+    The main function considers a minimal dataset containing biopsies 
     information in a specific format (described by a data dictionary), verifies 
-    its content and format (based on the data dictionary), assign diagnoses, and 
-    creates a summary report.
+    its content and format (based on the data dictionary), assigns diagnoses, 
+    and creates a summary report.
 License: GPL-3
 Depends: R (>= 3.4)
 URL: https://github.com/PersonalizedTransplantCare/banffIT

NEWS.md

@@ -1,14 +1,14 @@
 
 # banffIT 0.1.0
 
-The banffIT package provides provides functions to assign standardized
-diagnoses using the Banff Classification (Category 1 to 6 diagnoses,
-including Acute and Chronic active T-cell mediated rejection as well as
-Active, Chronic active, and Chronic antibody mediated rejection). The
-main function `banff_launcher()`considers a minimal dataset containing
+The banffIT package provides functions to assign standardized diagnoses
+using the Banff Classification (Category 1 to 6 diagnoses, including
+Acute and Chronic active T-cell mediated rejection as well as Active,
+Chronic active, and Chronic antibody mediated rejection). The main
+function `banff_launcher()`considers a minimal dataset containing
 biopsies information in a specific format (described by a data
 dictionary), verifies its content and format (based on the data
-dictionary), assign diagnoses, and create a summary report.
+dictionary), assigns diagnoses, and creates a summary report.
 
 ## Main functionality
 
@@ -30,7 +30,7 @@ dictionary), assign diagnoses, and create a summary report.
   its format and content based on the accepted format specified in the
   data dictionary.
 
-- `calculate_adequacy()` A tibble object with two columns: the
+- `calculate_adequacy()` A tibble object with two variables: the
   calculated adequacy (adequacy_calculated) and the adequacy specified
   in input (adequacy_input).
 
@@ -44,7 +44,7 @@ dictionary), assign diagnoses, and create a summary report.
 
 - `get_banff_dictionary()`, `get_banff_example()`,
   `get_banff_template()` This function gets the data dictionary used to
-  control the consistency of the Banff dataset, a example dataset and a
+  control the consistency of the input dataset, a example dataset and a
   template.
 
 - function `banffIT_website()` This function sends the user to the

R/01_utils.R

@@ -3,15 +3,16 @@
 #'
 #' @description
 #' This function gets the data dictionary used to control the consistency of
-#' the Banff dataset.
+#' the input dataset.
 #'
-#' @param which Indicates which Banff dictionary to get. Either "input" or
-#' "output". If NULL, both Banff dictionary are provided.
+#' @param which Indicates which variables to get from the Banff data dictionary.
+#' If NULL both input and output variables are provided.*
 #' @param language Optional input allowing the user to get the diagnoses in a
 #' specific language. Options are "label:en" (default), "label:fr", "label:de",
 #' "label:sp", "label:nl", "label:jp", "label:in".
-#' @param detail Whether the output should include temporary variables generated
-#' in the process or not. FALSE by default.
+#' @param detail Optional argument indicating whether the data dictionary should
+#' include temporary variables generated in the process or not.
+#' FALSE by default.
 #'
 #' @return
 #' A list of tibbles representing meta data used in the process. The metadata
@@ -114,7 +115,7 @@ The possible `language` are : ",toString(labels))
 }
 
 #' @title
-#' Get the Banff dataset example
+#' Get a dataset example
 #'
 #' @description
 #' This function gets the dataset used in the vignette as an example.
@@ -142,10 +143,10 @@ get_banff_example <- function(){
 }
 
 #' @title
-#' Get the Banff dataset template
+#' Get a dataset template
 #'
 #' @description
-#' This function gets the empty dataset with columns that are mandatory in the
+#' This function gets the empty dataset with variables that are mandatory in the
 #' process.
 #'
 #' @return

R/02_banff_launcher.R

@@ -22,9 +22,10 @@
 #' specific language. Options are "label:en" (default), "label:fr", "label:de",
 #' "label:sp", "label:nl", "label:jp", "label:in".
 #' @param option_filter Optional argument allowing the user to filter the
-#' dataset using [dplyr::filter()] syntax. The column used to filter must exist.
-#' @param detail Optional argument indicating whether the output should include
-#' temporary variables generated in the process or not. FALSE by default.
+#' dataset using [dplyr::filter()] syntax. The variable used to filter must
+#' exist.
+#' @param detail Optional argument indicating whether the output should
+#' include temporary variables generated in the process or not. FALSE by default.
 #'
 #' @return
 #' Nothing to be returned. The function generates a folder (if not already
@@ -142,7 +143,7 @@ Diagnoses for this file already exists in '",basename(output_folder),"'")
 
   message("\n[2/6] - Evaluation of '",bold(input_file_name),"'")
 
-  ##### evaluation of Banff dataset input.
+  ##### evaluation of input dataset.
   banff_assessment <-
     suppressMessages(banff_dataset_evaluate(banff_dataset))
 
@@ -222,8 +223,8 @@ For further information please refer to documentation.")
 
   banff_report$`Dataset assessment - diagnoses` <-
     banff_report$`Dataset assessment - diagnoses` %>%
-    select("column" = "name","condition" = "Quality assessment comment", "value") %>%
-    dplyr::filter(!.data$`column` %in% banff_report$`Dataset assessment - input`$column)
+    select("variable" = "name","condition" = "Quality assessment comment", "value") %>%
+    dplyr::filter(!.data$`variable` %in% banff_report$`Dataset assessment - input`$variable)
 
   banff_report <- banff_report[unique(c(
     "Overview","Dataset assessment - input",
@@ -236,7 +237,7 @@ For further information please refer to documentation.")
 
 The assessment and addition of diagnoses on your dataset is now finished.
 In the output folder, you will find an Excel file containing both labels and codes
-of your dataset and for each participant, additional columns corresponding to the
+of your dataset and for each participant, additional variables corresponding to the
 diagnoses.
 
 An assessment and summary report has been generated in your output folder to help you

R/03_algorithm.R

@@ -10,7 +10,7 @@
 #' @param banff_dataset A tibble object.
 #'
 #' @return
-#' A tibble object that contains additional columns with the diagnoses results.
+#' A tibble object that contains additional variables with the diagnoses results.
 #'
 #' @examples
 #' {
@@ -440,17 +440,17 @@ Use `banff_dataset_evaluate(banff_dataset)` to help you correcting your file.\n"
 }
 
 #' @title
-#' Calculate adequacy of each biopsy from glomeruli and arteries
+#' Calculate adequacy of each biopsy from glomeruli and arteries variables
 #'
 #' @description
-#' This function calculates adequacy of each biopsy (i.e., each observation) based on glomeruli and
-#' arteries variables (if provided).
+#' This function calculates adequacy of each biopsy (i.e., each observation)
+#' based on glomeruli and arteries variables (if provided).
 #'
 #' @param banff_dataset A tibble object.
 #'
 #' @return
-#' A tibble object with two columns: the calculated adequacy (adequacy_calculated)
-#' and the adequacy specified in input (adequacy_input).
+#' A tibble object with two variables: the calculated adequacy
+#' (adequacy_calculated) and the adequacy specified in input (adequacy_input).
 #'
 #' @examples
 #' {