# HG changeset patch
# User bornea
# Date 1461958931 14400
# Node ID a5444c834e72a502c79f307d509997a8721ff6ad
# Parent  0c0abdfad3b7d74d64867ce0d967dba88a03dafb
Uploaded

diff -r 0c0abdfad3b7 -r a5444c834e72 CRAPomeQuery.py
--- a/CRAPomeQuery.py	Mon Apr 25 11:47:05 2016 -0400
+++ b/CRAPomeQuery.py	Fri Apr 29 15:42:11 2016 -0400
@@ -5,12 +5,6 @@
 @author: brentkuenzi
 """
 ################################################################################
-## Dependencies ##
-import urllib2
-import sys
-import numpy
-import os
-################################################################################
 # This program will read in a SAINT formatted 'prey.txt' file or a file
 # containing a single column list of uniprot accessions (e.g. "P00533" or 
 # "EGFR_HUMAN")query the CRAPome database (v1.1), and return a file specifying 
@@ -24,6 +18,12 @@
 # A copy of the license is included in the section entitled "GNU
 # Free Documentation License".
 ################################################################################
+## Dependencies ##
+import urllib2
+import sys
+import numpy
+import os
+################################################################################
 ## REQUIRED INPUT ##
 # 1) crappyData: Prey.txt or single column list of Uniprot accessions
 crappyData = sys.argv[1] # Prey file or File with single column of accessions
@@ -33,9 +33,9 @@
 ################################################################################
 ## Global Variables ##
 if species == "HUMAN":
-    database = str(db_path) + "Human_CRAPome_v1-1.txt"
+    database = "Human_CRAPome_v1-1.txt"
 if species == "YEAST":
-    database = str(db_path) + "Yeast_CRAPome_v1-1.txt"
+    database = "Yeast_CRAPome_v1-1.txt"
 ################################################################################
 ## CRAPomeQuery ##
 class ReturnValue1(object):
@@ -134,7 +134,7 @@
             temp.append(i[0]) # append gene name
             ave = []
             total = len(i[3:]) # calculate total experiments
-            for j in i[3:]:
+            for j in i[3:]: 
                 if j != '0':
                     ave.append(int(j)) # calculate Ave.SC on only experiments with ID
                     cnt+=1
@@ -148,9 +148,6 @@
         else:
             temp.append(i[2]) # append accession
             temp.append(i[3])
-            temp.append("NA")
-            temp.append("NA")
-            temp.append("NA")
         query.append(temp) # final query results
 
     header = ["User Input","Mapped Gene Symbol","Num of Expt. (found/total)","Ave SC","Max SC"]