Fix the same issue as in preceding commits (hardcoded row numbers with respect...

Fix the same issue as in preceding commits (hardcoded row numbers with respect to median / count data) but for CSV inputs.

FUNCTIONS.R

@@ -61,21 +61,33 @@ runRelativeAntibodyUnits = function(fname1, fname2, MFI_CSV, MFI_N_ANTIGENS, TEM
   if(MFI_CSV){
     
     # Updated reading
-    L <- data.frame(read.csv(fname1,
-                             header=T, 
-                             stringsAsFactors=FALSE,
-                             colClasses=c(rep("character",3+as.integer(MFI_N_ANTIGENS))),
-                             na.string=c("")))
+    L_full <- data.frame(read.csv(fname1,
+                                  header=T,
+                                  stringsAsFactors=FALSE,
+                                  colClasses=c(rep("character",3+as.integer(MFI_N_ANTIGENS))),
+                                  na.string=c("")))
     
-    # Identify first row
-    ROW_N = match("Location", L[,1])
+    # Identify rows
+    median_row_number <- which(L_full[,2] == "Median")
+    count_row_number <- which(L_full[,2] == "Count")
+    endcount_row_number <- which(L_full[,2] == "Avg Net MFI")
     
     # Select data
-    L = L[ROW_N:(ROW_N+96),1:(3+as.integer(MFI_N_ANTIGENS))]
+    L = L_full[(median_row_number+1):nrow(L_full),1:(3+as.integer(MFI_N_ANTIGENS))]
     # the first row will be the header
     colnames(L) = L[1, ] 
     # removing the first row.
     L = L[-1, ]     
+    
+    ## Find all blank rows (i.e. rows that are all NA).
+    ## Then keep rows preceding the first blank row.
+    blank.row.number <- which(rowSums(is.na(L)) == length(names(L)))[1]
+    if(is.na(blank.row.number)){
+      L = L
+    }else{
+      L <- L[1:(blank.row.number-1),]
+    }
+    
     ## Exclude column that corresponds to "Total events"
     L <- L[, !(colnames(L) %in% c("Total Events","TotalEvents"))]
     
@@ -92,16 +104,7 @@ runRelativeAntibodyUnits = function(fname1, fname2, MFI_CSV, MFI_N_ANTIGENS, TEM
     L[,-which(colnames(L) %in% c("Location","Sample","Total Events","TotalEvents"))] = lapply(L[,-which(colnames(L) %in% c("Location","Sample","Total Events"))], as.numeric)
     
     ## Load the counts to check for run quality control
-    C <-  data.frame(read.csv(fname1,
-                              header=T, 
-                              stringsAsFactors=FALSE,
-                              colClasses=c(rep("character",3+as.integer(MFI_N_ANTIGENS))),
-                              na.string=c("")))
-    
-    # Row
-    ROW_C = 239
-    # Select data
-    C = C[ROW_C:(ROW_C+nrow(L)),1:(3+as.integer(MFI_N_ANTIGENS))]
+    C = L_full[(count_row_number+1):(count_row_number+1+nrow(L)),1:(3+as.integer(MFI_N_ANTIGENS))]
     # the first row will be the header
     colnames(C) = C[1, ] 
     # removing the first row.