--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/CloudMap_InSilico.py	Thu Nov 01 19:25:47 2012 -0400
@@ -0,0 +1,161 @@
+#!/usr/bin/python
+
+import sys
+import optparse
+import csv
+import operator
+import pprint
+
+def main():
+	parser = optparse.OptionParser()
+	parser.add_option("-i", dest = "input_files", action = "callback", callback = split_input_files)
+	parser.add_option("-n", dest = "sample_names", action = "callback", callback = split_sample_names)
+	parser.add_option("-s", dest = "summary_output_file", action = "store", type = "string")
+	parser.add_option("-o", dest = "data_output_file", action = "store", type = "string")
+	(options, args) = parser.parse_args()
+
+	#get the counts
+	gene_count = {}
+	for input_file in options.input_files:
+		gene_count = summarize_counts(input_file = input_file, gene_count = gene_count)
+	
+	#delete the single counts
+	for k, v in gene_count.items():
+		if v == 1:
+			del gene_count[k]
+
+	# we do two passes because we don't know the order yet and don't want to hold onto everything in memory
+
+	file_sample_dictionary = create_file_sample_dictionary(input_files = options.input_files, sample_names = options.sample_names)
+
+	#get snpeff lines
+	gene_data = {}
+	all_headers = []
+	for input_file in options.input_files:
+		headers = []
+		headers, gene_data = grab_snpeff_data(input_file = input_file, gene_data = gene_data, gene_count = gene_count, file_sample_dictionary = file_sample_dictionary)
+		
+		if len(all_headers) == 0 :
+			all_headers.extend(headers)
+
+	sorted_gene_count_list = sorted(gene_count.iteritems(), key = operator.itemgetter(1))
+	sorted_gene_count_list.reverse()
+
+	print_summary(gene_count_list = sorted_gene_count_list, summary_output_file = options.summary_output_file)
+	print_sorted_snpeff_data(gene_data = gene_data, gene_count_list = sorted_gene_count_list, data_output_file = options.data_output_file, all_headers = all_headers)
+
+def create_file_sample_dictionary(input_files = None, sample_names = None):
+	file_sample_dictionary = {}
+
+	for i in range(0, len(input_files)):
+		if i < len(sample_names):
+			file_sample_dictionary[input_files[i]] = sample_names[i]
+		else:
+			file_sample_dictionary[input_files[i]] = ""
+
+	return file_sample_dictionary
+		
+def split_input_files(option, opt_str, value, parser):
+	input_files = [] 
+	collect = True  
+	for i in range(0, len(parser.rargs)):
+		if "-s" == parser.rargs[i] or "-o" == parser.rargs[i] or "-n" == parser.rargs[i]:
+			collect = False
+		elif collect == True:
+			input_files.append(parser.rargs[i])
+
+	setattr(parser.values, option.dest, input_files)
+
+def split_sample_names(option, opt_str, value, parser):
+	input_files = [] 
+	collect = True  
+	for i in range(0, len(parser.rargs)):
+		if "-s" == parser.rargs[i] or "-o" == parser.rargs[i] or "-i" == parser.rargs[i]:
+			collect = False
+		elif collect == True:
+			input_files.append(parser.rargs[i])
+
+	setattr(parser.values, option.dest, input_files)
+
+
+def print_summary(gene_count_list = None, summary_output_file = ""):
+	f = open(summary_output_file, 'w')
+	f.write('\n'.join('%s\t%s' % g for g in gene_count_list))
+	f.close()
+
+def print_sorted_snpeff_data(gene_data = {}, gene_count_list = None, data_output_file = "", file_sample_dictionary = None, all_headers = None):
+	f = open(data_output_file, 'w')
+
+	for header in all_headers:
+		f.write('Sample Name')
+		f.write('\t')
+		f.write(('\t').join(header))
+		f.write('\n')
+
+	for i in range(0, len(gene_count_list)):
+		gene_id = gene_count_list[i][0]
+		f.write(gene_data[gene_id] + "\n")
+
+	f.close()
+
+def grab_snpeff_data(input_file = "", gene_data = {}, gene_count = {}, file_sample_dictionary = None):
+	i_file = open(input_file, 'rU')
+	reader = csv.reader(i_file, delimiter = '\t')
+	headers = skip_and_collect_headers(reader = reader, i_file = i_file)
+
+	sample_name = file_sample_dictionary[input_file]
+
+	for row in reader:
+		gene_id = row[9].upper()
+		if gene_id in gene_count:
+			if gene_id in gene_data:
+				gene_data[gene_id] = gene_data[gene_id] + '\n' + sample_name + '\t' + '\t'.join(row).rstrip()
+			else:
+				gene_data[gene_id] = sample_name + '\t' + '\t'.join(row).rstrip()
+
+	return headers, gene_data
+
+def summarize_counts(input_file= "", gene_count = {}):
+	i_file = open(input_file, 'rU')
+	reader = csv.reader(i_file, delimiter = '\t')
+	skip_and_collect_headers(reader = reader, i_file = i_file)
+
+	counted_genes = []
+
+	for row in reader:
+		gene_id = row[9].upper()
+		if gene_id not in counted_genes:
+			if gene_id in gene_count and gene_id not in counted_genes:
+				gene_count[gene_id] += 1
+			else:
+				gene_count[gene_id] = 1
+			
+			counted_genes.append(gene_id)
+
+	return gene_count
+	
+def skip_and_collect_headers(reader = None, i_file = None):
+	headers = []	
+
+	# count headers
+	comment = 0
+	while True:
+		row = reader.next()
+		if len(row) == 0:
+			comment = comment + 1
+		elif row[0].startswith('#'):
+			comment = comment + 1
+			if comment == 3:
+				headers.append(row)
+		else:
+			break
+	
+	# skip headers
+	i_file.seek(0)
+	for i in range(0, comment):
+		reader.next()
+
+	return headers
+
+if __name__ == "__main__":
+	main()