muscope.py

#!/usr/bin/env python3
import os
import csv
import argparse

parser = argparse.ArgumentParser(description='Process output from Mash')
parser.add_argument('-i', '--input',    help='input file',     metavar='FILE',   required=True)
parser.add_argument('-o', '--output',   help='output file',    metavar='FILE'                 )
parser.add_argument('-a', '--alias',    help='alias file',     metavar='FILE'                 )
parser.add_argument('-n', '--nearness', help='invert distance',action="store_true"            )
args = parser.parse_args()

aliases = {}
if args.alias is not None:
	with open(args.alias,'rb') as alias_file:
		aliases = dict(csv.reader(alias_file, delimiter='\t', quotechar='|'))
		##### While the above will work, you should really do more checking on the alias file. Something like this:
		#for alias_line, alias_data in enumerate(csv.reader(alias_file, delimiter='\t', quotechar='|')):
		#   if len(alias_data) == 2:
		#      alias_from,alias_to = alias_data
		#      if alias_from in aliases.keys():   print 'ERROR: Line',alias_line+1,'in alias file',args.alias,'contained an alias previously mapped!'; exit()
		#      if alias_to   in aliases.values(): print 'ERROR: Line',alias_line+1,'in alias file',args.alias,'wants to map',alias_from,'to',alias_to,'but the latter has already been assigned!'; exit()
		#      aliases[alias[0]] = alias[1]
		#   else:                                 print 'ERROR: Line',alias_line+1,'in alias file',args.alias,'contained more than two columns!'; exit()

if args.output is None:
	path,extension = os.path.splitext(os.path.abspath(os.path.expanduser(args.input)))
	args.output    = path +'.2' + extension

def clean_file_name(file_path):
	clean_name = os.path.basename(os.path.splitext(file_path)[0]) # I would remove all extensions
	return aliases[clean_name] if clean_name in aliases else clean_name

with open(args.input,'rb') as input_file, open(args.output,'wb') as output_file:
	input_csv  = csv.reader(input_file,  delimiter='\t', quotechar='|')
	output_csv = csv.writer(output_file, delimiter='\t', quotechar='|')
	output_csv.writerow( [clean_file_name(name) for name in next(input_csv)[1:]] ) #1: gets rid of the #query
	for input_data in input_csv:
		filename = [ clean_file_name(input_data[0]) ]
		if args.nearness: values = [1 - float(x) for x in input_data[1:]] # nearness is not a good choice of words, ideally you want something that makes sense in the context of "if X:" like "if do_invert:".
		else:             values = input_data[1:]
		output_csv.writerow(filename + values)

print "All done! See ", args.output

If you do not wish to remove all file extensions, then instead of using re.sub(r'\.fn?a(st[aq])?$', '', name) and similar, which no biologist would/should ever understand, I would just take the extension, and check if it is in a set of extensions you want to remove the extension of, and then decide to use the path with the extension or not. This will be faster and simpler for your users :)