--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/experimental_design/experimental_design.py	Mon Aug 29 05:41:20 2016 -0400
@@ -0,0 +1,50 @@
+import sys
+import pandas as pd
+
+def main():
+	patients = {}
+	files = []
+	sample_id = sys.argv[1]
+	imgt_files = 0
+	blast_files = 0
+	#organize files
+	for arg in sys.argv[2:-2]:
+		if arg.find("/") is -1:
+			patients[sample_id] = files
+			files = []
+			sample_id = arg
+		else:
+			df = pd.read_csv(arg, sep="\t", dtype=object, error_bad_lines=False)
+			if "Functionality" in list(df.columns.values):
+				df["VDJ Frame"][df["Functionality"] != "productive"] = "In-frame with stop codon"
+				imgt_files += 1
+			else:
+				blast_files += 1
+			files.append(df)
+	patients[sample_id] = files
+	columns = [u'ID', u'VDJ Frame', u'Top V Gene', u'Top D Gene', u'Top J Gene', u'CDR1 Seq', u'CDR1 Length', u'CDR2 Seq', u'CDR2 Length', 
+			   u'CDR3 Seq', u'CDR3 Length', u'CDR3 Seq DNA', u'CDR3 Length DNA', u'Strand', u'CDR3 Found How', u'Functionality', 'V-REGION identity %', 
+			   'V-REGION identity nt', 'D-REGION reading frame', 'AA JUNCTION', 'Functionality comment', 'Sequence', 'FR1-IMGT', 'FR2-IMGT', 
+			   'FR3-IMGT', 'CDR3-IMGT', 'JUNCTION', 'J-REGION', 'FR4-IMGT', 'P3V-nt nb', 'N1-REGION-nt nb', 'P5D-nt nb', 'P3D-nt nb', 'N2-REGION-nt nb', 
+			   'P5J-nt nb', '3V-REGION trimmed-nt nb', '5D-REGION trimmed-nt nb', '3D-REGION trimmed-nt nb', '5J-REGION trimmed-nt nb', u'Sample', u'Replicate']
+	if "N-REGION-nt nb" in files[0].columns:
+		columns.insert(30, "N-REGION-nt nb")
+	if blast_files is not 0:
+		print "Has a parsed blastn file, using limited columns."
+		columns = [u'ID', u'VDJ Frame', u'Top V Gene', u'Top D Gene', u'Top J Gene', u'CDR1 Seq', u'CDR1 Length', u'CDR2 Seq', u'CDR2 Length', u'CDR3 Seq', u'CDR3 Length', u'CDR3 Seq DNA', u'CDR3 Length DNA', u'Strand', u'CDR3 Found How', u'Sample', u'Replicate']
+
+	result = None
+	for patient_id, samples in patients.iteritems():
+		count = 1
+		for sample in samples:
+			sample['Sample'] = patient_id
+			sample['Replicate'] = str(count)
+			count += 1
+			if result is None:
+				result = sample[columns]
+			else:
+				result = result.append(sample[columns])
+	result.to_csv(sys.argv[-1], sep="\t", index=False, index_label="index")
+
+if __name__ == "__main__":
+	main()