--- a
+++ b/modules/CrossValidation/CVManager.py
@@ -0,0 +1,57 @@
+#CVManager.py
+"""
+ Deep Learning for Cancer Therapy
+
+ Authors:
+ Kumud Ravisankaran | Valeria Brewer
+ Ninad Mehta | Suraj Jena
+
+"""
+
+import sys
+from Status.Status import Status
+
+sys.path.append('../')
+sys.dont_write_bytecode = True
+
+class CVManager:
+    def __init__(self):
+        self.status = Status("CVManager")
+
+    def CrossValidate(self,List,folds,TestingQueue,TrainingQueue):
+        self.status.message(1,"CrossValidate(self,path,folds)")
+        List.printList()
+        # List will hold 10 nodes where the head is Testing and the other 9 nodes are Training data
+        for i in range(1,folds+1):
+            testingFold = List.head.get_data()
+            
+            if(i == 1):
+                path = testingFold[0:-10]
+
+            trainingFoldCSV = path +"trainingFold_%s.csv" % i
+            combine=open(trainingFoldCSV,"w")
+
+            testingFoldCSV = path+"testingFold_%s.csv" % i
+            testing=open(testingFoldCSV,"w")
+
+            trainingFold_1 = List.head.get_next().get_data()
+            currentFold = List.head.get_next()
+
+            for line in open(trainingFold_1):
+                combine.write(line)
+            for line in open(testingFold):
+                testing.write(line)
+            for num in range(2,folds):
+                currentFold = currentFold.get_next()
+                currentFoldData = currentFold.get_data()
+                single = open(currentFoldData)
+                #self.header = self.single.next()
+                for line in single:
+                    combine.write(line)
+                single.close()
+            combine.close()
+            TrainingQueue.put(trainingFoldCSV)
+            TestingQueue.put(testingFoldCSV)
+            List.updateList()
+
+        self.status.message(0,"CrossValidate(self,path,folds)")