diff --git a/scripts/7_normalization.Rmd b/scripts/7_normalization.Rmd
index f9e8abf..52297e2 100644
--- a/scripts/7_normalization.Rmd
+++ b/scripts/7_normalization.Rmd
@@ -31,7 +31,7 @@ knitr::opts_knit$set(root.dir = paste0(user_choices$personal_path, "/"))
 knitr::opts_chunk$set(echo = FALSE)
 
 if (user_choices$array_type == "v2") {
-  if (!("jokergoo/IlluminaHumanMethylationEPICv2manifest" %in% rownames(installed.packages()))) {
+  if (!("IlluminaHumanMethylationEPICv2manifest" %in% rownames(installed.packages()))) {
     BiocManager::install("jokergoo/IlluminaHumanMethylationEPICv2manifest")
   }
   if (!("IlluminaHumanMethylationEPICv2anno.20a1.hg38" %in% rownames(installed.packages()))) {
@@ -84,27 +84,22 @@ save(gRatioSet_clean_filtered_quantile, file = paste0(user_choices$project_name,
 
 Betas_clean_filtered_quantile <- getBeta(gRatioSet_clean_filtered_quantile)
 save(Betas_clean_filtered_quantile, file = paste0(user_choices$project_name, 
-                                         "/processed_data/Betas_clean_filtered_quantile.Rdata"))
-Ms_clean_filtered_qunatile <- getM(gRatioSet_clean_filtered_quantile)
-save(Ms_clean_filtered_qunatile, file = paste0(user_choices$project_name, 
-                                        "/processed_data/Ms_clean_filtered_qunatile.Rdata"))
+                                        "/processed_data/Betas_clean_filtered_quantile.Rdata"))
+Ms_clean_filtered_quantile <- getM(gRatioSet_clean_filtered_quantile)
+save(Ms_clean_filtered_quantile, file = paste0(user_choices$project_name, 
+                                        "/processed_data/Ms_clean_filtered_quantile.Rdata"))
 # further normalization with BMIQ:
-probeType <- as.data.frame(annotations_clean_filtered[rownames(Betas_clean_filtered_quantile),c("Name","Type")])
+probeType <- as.data.frame(subset(annotations_clean_filtered, Name %in% rownames(Betas_clean_filtered_quantile), select=c("Name","Type")))
 probeType$probeType = ifelse(probeType$Type %in% "I", 1, 2)
 Betas_clean_filtered_quantile_bmiq <- apply(Betas_clean_filtered_quantile[,1:length(colnames(Betas_clean_filtered_quantile))],2,
                                    function(a) BMIQ(a,probeType$probeType,plots=FALSE)$nbeta) # sourced from script "BMIQ_1.6_Teschendorff.R"
-save(Betas_clean_filtered_quantile_bmiq, file = paste0(user_choices$project_name,
-                                              "/processed_data/Betas_clean_filtered_quantile_bmiq.Rdata"))
+save(Betas_clean_filtered_quantile_bmiq, file = paste0(user_choices$project_name,                                             "/processed_data/Betas_clean_filtered_quantile_bmiq.Rdata"))
 
 ```
 
-```{r. normalize unfiltered probes, include=FALSE}
+```{r normalize unfiltered probes, include=FALSE}
 # Normalization of unfiltered data
-
-# Functional normalization 
-# Note: sex is set to "F" for all samples since sex chromosomes were already removed in script 6
-# Note: This does not affect the normalization or the phenotype data, it simply stops preprocessQuantile() from producing an error
-gRatioSet_clean_unfiltered_quantile <- preprocessQuantile(RGSet_clean, sex = "F")
+gRatioSet_clean_unfiltered_quantile <- preprocessQuantile(RGSet_clean)
 save(gRatioSet_clean_unfiltered_quantile, file = paste0(user_choices$project_name, 
                                          "/processed_data/gRatioSet_clean_unfiltered_quantile.Rdata")) # output: GenomicRatioSet