diff --git a/FUNCTIONS.R b/FUNCTIONS.R index aeb5cd6673014728f6cab164507d0785f527b743..e3bdc23e7562a437fcf43dc14556a103a356eb7a 100644 --- a/FUNCTIONS.R +++ b/FUNCTIONS.R @@ -103,7 +103,7 @@ runRelativeAntibodyUnits = function(fname1, fname2, MFI_CSV, MFI_N_ANTIGENS, TEM dim(L) # MFI values as numeric - L[,-which(colnames(L) %in% c("Location","Sample","Total Events","TotalEvents"))] = lapply(L[,-which(colnames(L) %in% c("Location","Sample","Total Events"))], as.numeric) + L[,-which(colnames(L) %in% c("Location","Sample","Total Events","TotalEvents"))] = lapply(L[,-which(colnames(L) %in% c("Location","Sample","Total Events","TotalEvents"))], as.numeric) ## Load the counts to check for run quality control C = L_full[(count_row_number+1):(count_row_number+1+nrow(L)),1:(3+as.integer(MFI_N_ANTIGENS))] @@ -177,7 +177,7 @@ runRelativeAntibodyUnits = function(fname1, fname2, MFI_CSV, MFI_N_ANTIGENS, TEM L <- L %>% mutate_all(funs(gsub("NaN", 0, .))) # MFI values as numeric - L[,-which(colnames(L) %in% c("Location","Sample","Total Events","TotalEvents"))] = lapply(L[,-which(colnames(L) %in% c("Location","Sample","Total Events"))], as.numeric) + L[,-which(colnames(L) %in% c("Location","Sample","Total Events","TotalEvents"))] = lapply(L[,-which(colnames(L) %in% c("Location","Sample","Total Events","TotalEvents"))], as.numeric) C <- as.data.frame(read_excel(fname1, skip = count_row_number+1, col_types = "text")) @@ -247,7 +247,7 @@ runRelativeAntibodyUnits = function(fname1, fname2, MFI_CSV, MFI_N_ANTIGENS, TEM C <- L %>% dplyr::mutate(dplyr::across(!c(Location, Sample), gsub, pattern = "^(\\d+(?:\\.\\d+)?)(\\s*\\((\\d+(?:\\.\\d+)?)\\))?$", replacement = "\\3")) %>% # Set to NA in case bead counts were not available - dplyr::mutate(dplyr::across(!Location & !Sample, gsub, pattern = "^$", replacement = NA)) + dplyr::mutate(dplyr::across(!c(Location, Sample), gsub, pattern = "^$", replacement = NA)) dim(C)