Replaced all RGSets with gRatioSets

scripts/6_filtering_cpgs.Rmd

@@ -105,9 +105,10 @@ if (user_choices$array_type == "v2") {
     filter(CpG_name %in% replicates$CpG_name) %>%
     filter(!(IlmnID %in% keep_replicates$IlmnID))
   
-  # exclude replicates from betas, RGSet, detP and save data
-  RGSet_clean <- subsetByLoci(RGSet_clean, excludeLoci = exclude_replicates$IlmnID)
-  save(RGSet_clean, file = paste0(user_choices$project_name, "/processed_data/RGSet_clean.Rdata"))
+  # exclude replicates from betas, gRatioSet, detP and save data
+  keep_gratioset <- !(featureNames(gRatioSet_clean) %in% exclude_replicates$IlmnID)
+  gRatioSet_clean <- gRatioSet_clean[keep_gratioset,]
+  save(gRatioSet_clean, file = paste0(user_choices$project_name, "/processed_data/gRatioSet_clean.Rdata"))
   
   keep_betas <- !(rownames(Betas_clean) %in% exclude_replicates$IlmnID) 
   Betas_clean <- Betas_clean[keep_betas,]
@@ -126,13 +127,13 @@ if (user_choices$array_type == "v2") {
   keep_betas_df <- as.data.frame(keep_betas)
   cat(paste0(nrow(exclude_replicates), " replicate probes were removed"))
   
-  dim_RGSet_filtered <- dim(RGSet_clean)
+  dim_gRatioSet_filtered <- dim(gRatioSet_clean)
   dim_Betas_filtered <- dim(Betas_clean)
   step_number <- c("4", "4")
   step <- c("Filter replicates", "Filter replicates")
-  data_class <- c("RGSet", "Betas")
-  samples <- c(dim_RGSet_filtered[2], dim_Betas_filtered[2])
-  probes <- c(dim_RGSet_filtered[1], dim_Betas_filtered[1])
+  data_class <- c("gRatioSet", "Betas")
+  samples <- c(dim_gRatioSet_filtered[2], dim_Betas_filtered[2])
+  probes <- c(dim_gRatioSet_filtered[1], dim_Betas_filtered[1])
 
   table_preprocessing_adding <- data.frame(step_number, step, data_class, samples, probes)
   summary_table_preprocessing <- bind_rows(summary_table_preprocessing, table_preprocessing_adding)
@@ -371,7 +372,8 @@ if (user_choices$array_type == "v2") {
   keep_betas <- !(rownames(Betas_clean_filtered) %in% v2_mapping_inacc$IlmnID)
   Betas_clean_filtered <- Betas_clean_filtered[keep_betas,]
   
-  RGSet_clean_filtered <- subsetByLoci(RGSet_clean_filtered, excludeLoci = v2_mapping_inacc$IlmnID)
+  keep_gratioset <- !(featureNames(gRatioSet_clean_filtered) %in% v2_mapping_inacc$IlmnID) 
+  gRatioSet_clean_filtered <- gRatioSet_clean_filtered[keep_gratioset,]
 }
 ```
 
@@ -381,13 +383,13 @@ if (user_choices$array_type == "v2") {
   cat(paste0(keep_betas_df %>% filter(keep_betas == FALSE) %>% nrow(), 
              " CpGs show known mapping inaccuracies"), sep = "<br>\n")
   
-  dim_RGSet_filtered <- dim(RGSet_clean_filtered)
+  dim_gRatioSet_filtered <- dim(gRatioSet_clean_filtered)
   dim_Betas_filtered <- dim(Betas_clean_filtered)
   step_number <- c("12", "12")
   step <- c("Filter Mapping Inaccuracies", "Filter Mapping Inaccuracies")
-  data_class <- c("RGSet", "Betas")
-  samples <- c(dim_RGSet_filtered[2], dim_Betas_filtered[2])
-  probes <- c(dim_RGSet_filtered[1], dim_Betas_filtered[1])
+  data_class <- c("gRatioSet", "Betas")
+  samples <- c(dim_gRatioSet_filtered[2], dim_Betas_filtered[2])
+  probes <- c(dim_gRatioSet_filtered[1], dim_Betas_filtered[1])
   
   table_preprocessing_adding <- data.frame(step_number, step, data_class, samples, probes)
   summary_table_preprocessing <- bind_rows(summary_table_preprocessing, table_preprocessing_adding)
@@ -401,7 +403,8 @@ if (user_choices$array_type == "v2") {
   keep_betas <- !(rownames(Betas_clean_filtered) %in% v2_flagged_probes$IlmnID)
   Betas_clean_filtered <- Betas_clean_filtered[keep_betas,]
   
-  RGSet_clean_filtered <- subsetByLoci(RGSet_clean_filtered, excludeLoci = v2_flagged_probes$IlmnID)
+  keep_gratioset <- !(featureNames(gRatioSet_clean_filtered) %in% v2_flagged_probes$IlmnID) 
+  gRatioSet_clean_filtered <- gRatioSet_clean_filtered[keep_gratioset,]
 }
 ```
 
@@ -411,13 +414,13 @@ if (user_choices$array_type == "v2") {
   cat(paste0(keep_betas_df %>% filter(keep_betas == FALSE) %>% nrow(), 
              " CpGs were flagged by Illumina"), sep = "<br>\n")
   
-  dim_RGSet_filtered <- dim(RGSet_clean_filtered)
+  dim_gRatioSet_filtered <- dim(gRatioSet_clean_filtered)
   dim_Betas_filtered <- dim(Betas_clean_filtered)
   step_number <- c("13", "13")
   step <- c("Filter Flagged Probes", "Filter Flagged Probes")
-  data_class <- c("RGSet", "Betas")
-  samples <- c(dim_RGSet_filtered[2], dim_Betas_filtered[2])
-  probes <- c(dim_RGSet_filtered[1], dim_Betas_filtered[1])
+  data_class <- c("gRatioSet", "Betas")
+  samples <- c(dim_gRatioSet_filtered[2], dim_Betas_filtered[2])
+  probes <- c(dim_gRatioSet_filtered[1], dim_Betas_filtered[1])
   
   table_preprocessing_adding <- data.frame(step_number, step, data_class, samples, probes)
   summary_table_preprocessing <- bind_rows(summary_table_preprocessing, table_preprocessing_adding)