library path added and detp descrtiption specified

scripts/1_definitions_and_setup.Rmd

@@ -33,7 +33,7 @@ This script asks the user to define or choose:
 * project name  
 * array type  
 * population ethnicity  
-* detection *p* value limit (script 4 will exclude samples with *p* values higher than this value)  
+* detection *p* value limit for samples (script 4 will exclude samples with *p* values higher than this value)  
 * extreme outliers definition (number of standard deviation of first and second PCA for script 10)  
 * the name of the following columns as they are written in your phenotype data: 
   + slide (example: "201715340007")  
@@ -52,12 +52,16 @@ The path name should not include the name of the github repository
 **Path to phenotype data:** The path to the data table containing phenotype information  
 The path name should include the name of data table itself. This file must be **.csv**  
 **Path to idat files:** The path to the raw files obtained from array  
+**Path to R package directories (optional):** The path to the personal directory for installing and loading packages. 
+This is needed if installation of R packages to the default R library are not permitted due to the lack of admin rights. 
+Thsi will enable R to install and load any needed packages without problems. 
+Please make sure you have the needed writing permissions in this specified directory  
 **Array type:** "v1" or "v2". This stands for the different versions of the EPIC array  
 **Population ethnicity:** Choose "AFR", "AMR", "ASN", "EUR" or "Global". Global 
 may be used if the population is very diverse. This information will be useful for removing 
 ethnic-specific hybridizing probes  
-**Detection p-value:** The threshold for the *p* value of detection. This *p* value indicates the
-signal quality in the initial Quality Control (QC) (we typically use a 
+**Detection p-value of samples:** The threshold for the *p* value of detection. This *p* value indicates the
+signal quality in the initial Quality Control (QC) for samples (we typically use a 
 threshold of 0.05 and set this by default)  
 **Define extreme outliers:** We define outliers as outside a certain number of standard deviations from the mean 
 in the first and second principal component. You choose how many standard deviations 
@@ -104,10 +108,11 @@ The following information is required:
 personal_path <- "PLEASE FILL IN"
 pheno_path <- "PLEASE FILL IN"
 idat_path <- "PLEASE FILL IN"
+package_path <- "PLEASE FILL IN"
 project_name <- "PLEASE FILL IN"
 array_type <- "PLEASE FILL IN"
 population_ethnicity <- "PLEASE FILL IN"
-detP_threshold <- "0.05"
+detP_sample_threshold <- "0.05"
 outlier_threshold <- "3"
 name_slide_column <- "PLEASE FILL IN"
 name_array_column <- "PLEASE FILL IN"
@@ -118,6 +123,7 @@ name_sex_column <- "PLEASE FILL IN"
 additional_batch_variable_1 <- "PLEASE FILL IN"
 additional_batch_variable_2 <- "PLEASE FILL IN"
 additional_batch_variable_3 <- "PLEASE FILL IN"
+
 ```
 
 ```{r, save user choices, include=FALSE}
@@ -128,7 +134,7 @@ user_choices <- data.frame(
   "project_name" = project_name,
   "array_type" = array_type,
   "population_ethnicity" = population_ethnicity,
-  "detP_threshold" = as.numeric(detP_threshold),
+  "detP_sample_threshold" = as.numeric(detP_sample_threshold),
   "outlier_threshold" = as.numeric(outlier_threshold),
   "name_slide_column" = name_slide_column,
   "name_array_column" = name_array_column,
@@ -152,6 +158,9 @@ ifelse(pheno_path == "PLEASE FILL IN",
 ifelse(idat_path == "PLEASE FILL IN", 
        idat_path_message <- "✘ Please specify the path to idat files", 
        idat_path_message <- "✔ Path to idat files was provided")
+ifelse(package_path == "PLEASE FILL IN", 
+       package_path_message <- "✔ Package installation path was not specified and therefore default path will be used", 
+       package_path_message <- paste0("✔ Package installation path was specified: ", package_path, ". all R packages will be installed here."))
 ifelse(project_name == "PLEASE FILL IN", 
        project_name_message <- "✘ Please specify project name", 
        project_name_message <- "✔ Project name was provided")
@@ -163,9 +172,9 @@ ifelse(population_ethnicity %in% c("AFR", "AMR", "ASN", "EUR", "Global"),
        population_ethnicity_message <- "✔ Population ethnicity is OK", 
        population_ethnicity_message <- paste0("✘ This population ethnicity is not available: ", 
                     population_ethnicity, ". Please use AFR, AMR, ASN, EUR or Global"))
-ifelse(detP_threshold == "0.05" | detP_threshold == "0.01", 
-       detP_threshold_message <- "✔ Detection p-value is OK", 
-       detP_threshold_message <- paste0("✘ This detection p-value is not available: ", detP_threshold, ". Please use 0.05 or 0.01"))
+ifelse(detP_sample_threshold == "0.05" | detP_sample_threshold == "0.01", 
+       detP_sample_threshold_message <- "✔ Detection p-value is OK", 
+       detP_sample_threshold_message <- paste0("✘ This detection p-value is not available: ", detP_sample_threshold, ". Please use 0.05 or 0.01"))
 ifelse(outlier_threshold == "3",
        outlier_threshold_message <- "✔ Outlier threshold is set to standard: 3 standard deviations", 
        outlier_threshold_message <- paste0("✔ New outlier threshold was set to be: ", outlier_threshold, " standard deviations"))
@@ -225,9 +234,9 @@ user_choices %>% paged_table()
 ## Check user definitions
 
 ```{r, users definitions check, results = 'asis'}
-cat(personal_path_message, pheno_path_message, idat_path_message, 
+cat(personal_path_message, pheno_path_message, idat_path_message, package_path_message,
     project_name_message, array_type_message, population_ethnicity_message,
-    detP_threshold_message, outlier_threshold_message, phenotype_names_message, 
+    detP_sample_threshold_message, outlier_threshold_message, phenotype_names_message, 
     additional_batch_variables_message,
     sep = "<br>\n")
 ```