diff --git a/R/tune.spca.R b/R/tune.spca.R
index 1b9eece6..51c4f14e 100644
--- a/R/tune.spca.R
+++ b/R/tune.spca.R
@@ -76,6 +76,24 @@ tune.spca <- function(X,
                     ## split data to train/test
                     X.train = X[-test.fold.inds,,drop=FALSE]
                     X.test = X[test.fold.inds,,drop=FALSE]
+                    
+                    
+                    
+                    # find indices of rows in X.train that contain NAs
+                    rows.NAs.train <- rowSums(is.na(X.train))
+                    rows.NAs.train <- which(rownames(X.train) %in% names(rows.NAs.train[rows.NAs.train!= 0]))
+                    
+                    # find indices of rows in X.test that contain NAs
+                    rows.NAs.test <- rowSums(is.na(X.test))
+                    rows.NAs.test <- which(rownames(X.test) %in% names(rows.NAs.test[rows.NAs.test!= 0]))
+                    
+                    # if there are rows with NAs, remove them from the appropriate sets
+                    if (length(rows.NAs.train)>0) {X.train <- X.train[-rows.NAs.train,]}
+                    if (length(rows.NAs.test)>0) {
+                        X.test <- X.test[-rows.NAs.test,]
+                        t.comp.actual <- t.comp.actual[-rows.NAs.test]
+                    }
+                    
                     # ---- run sPCA 
                     ## train
                     spca.train = spca(X.train, ncomp = ncomp, keepX = c(keepX.opt, keepX.value), center = center, scale = FALSE)