--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/unipept.py	Fri Apr 03 14:55:49 2015 -0400
@@ -0,0 +1,194 @@
+#!/usr/bin/env python
+"""
+#
+#------------------------------------------------------------------------------
+#                         University of Minnesota
+#         Copyright 2015, Regents of the University of Minnesota
+#------------------------------------------------------------------------------
+# Author:
+#
+#  James E Johnson
+#
+#------------------------------------------------------------------------------
+"""
+
+import json
+import logging
+import optparse
+from optparse import OptionParser
+import os
+import sys
+import re
+import urllib
+import urllib2
+try:
+    import xml.etree.cElementTree as ET
+except ImportError:
+    import xml.etree.ElementTree as ET
+
+def warn_err(msg,exit_code=1):
+    sys.stderr.write(msg)
+    if exit_code:
+      sys.exit(exit_code)
+
+def read_fasta(fp):
+    name, seq = None, []
+    for line in fp:
+        line = line.rstrip()
+        if line.startswith(">"):
+            if name: yield (name, ''.join(seq))
+            name, seq = line, []
+        else:
+            seq.append(line)
+    if name: yield (name, ''.join(seq))
+
+def read_mzid(fp):
+  peptides = []
+  for event, elem in ET.iterparse(fp):
+    if event == 'end':
+      if re.search('PeptideSequence',elem.tag):
+        peptides.append(elem.text)
+  return peptides
+
+def read_pepxml(fp):
+  peptides = []
+  for event, elem in ET.iterparse(fp):
+    if event == 'end':
+      if re.search('search_hit',elem.tag):
+        peptides.append(elem.get('peptide'))
+  return peptides
+
+def __main__():
+  #Parse Command Line
+  parser = optparse.OptionParser()
+  # unipept API
+  parser.add_option( '-A', '--api', dest='unipept', default='pept2lca', choices=['pept2lca','pept2taxa','pept2prot'], help='The unipept application: pept2lca, pept2taxa, or pept2prot' )
+  # files
+  parser.add_option( '-t', '--tabular', dest='tabular', default=None, help='A tabular file that contains a peptide column' )
+  parser.add_option( '-c', '--column', dest='column', type='int', default=0, help='The column (zero-based) in the tabular file that contains peptide sequences' )
+  parser.add_option( '-f', '--fasta', dest='fasta', default=None, help='A fasta file containing peptide sequences' )
+  parser.add_option( '-m', '--mzid', dest='mzid', default=None, help='A mxIdentML file containing peptide sequences' )
+  parser.add_option( '-p', '--pepxml', dest='pepxml', default=None, help='A pepxml file containing peptide sequences' )
+  # Unipept Flags
+  parser.add_option( '-e', '--equate_il', dest='equate_il', action='store_true', default=False, help='isoleucine (I) and leucine (L) are equated when matching tryptic peptides to UniProt records' )
+  parser.add_option( '-x', '--extra', dest='extra', action='store_true', default=False, help='return the complete lineage of the taxonomic lowest common ancestor' )
+  parser.add_option( '-n', '--names', dest='names', action='store_true', default=False, help='return the names of all ranks in the lineage of the taxonomic lowest common ancestor' )
+  # Warn vs Error Flag
+  parser.add_option( '-S', '--strict', dest='strict', action='store_true', default=False, help='Print exit on invalid peptide' )
+  # outputs
+  parser.add_option( '-J', '--json', dest='json', default=None, help='Output file path for json formatted results')
+  parser.add_option( '-T', '--tsv', dest='tsv', default=None, help='Output file path for TAB-separated-values (.tsv) formatted results')
+  parser.add_option( '-C', '--csv', dest='csv', default=None, help='Output file path for Comma-separated-values (.csv) formatted results')
+  parser.add_option( '-M', '--mismatch', dest='mismatch', default=None, help='Output file path for peptide with no matches' )
+  (options, args) = parser.parse_args()
+  invalid_ec = 2 if options.strict else None
+  peptides = []
+  pep_pat = '^([ABCDEFGHIKLMNPQRSTVWXYZ]+)$'
+  ## Get peptide sequences
+  if options.mzid:
+    peptides += read_mzid(options.mzid)
+  if options.pepxml:
+    peptides += read_pepxml(options.pepxml)
+  if options.tabular:
+    with open(options.tabular) as fp:
+      for i,line in enumerate(fp):
+        if line.strip() == '' or line.startswith('#'):
+          continue
+        fields = line.rstrip('\n').split('\t')
+        peptide = fields[options.column]
+        if not re.match(pep_pat,peptide):
+          warn_err('"%s" is not a peptide (line %d column %d of tabular file: %s)\n' % (peptide,i,options.column,options.tabular),exit_code=invalid_ec)
+        peptides.append(peptide) 
+  if options.fasta:
+    with open(options.fasta) as fp:
+      for id, peptide in read_fasta(fp):
+        if not re.match(pep_pat,peptide):
+          warn_err('"%s" is not a peptide (id %s of fasta file: %s)\n' % (peptide,id,options.fasta),exit_code=invalid_ec)
+        peptides.append(peptide) 
+  if args and len(args) > 0:
+    for i,peptide in enumerate(args):
+      if not re.match(pep_pat,peptide):
+        warn_err('"%s" is not a peptide (arg %d)\n' % (peptide,i),exit_code=invalid_ec)
+      peptides.append(peptide) 
+  if len(peptides) < 1:
+    warn_err("No peptides input!",exit_code=1)
+  ## unipept
+  post_data = []
+  if options.equate_il:
+    post_data.append(("equate_il","true"))
+  if options.names:
+    post_data.append(("extra","true"))
+    post_data.append(("names","true"))
+  elif options.extra:
+    post_data.append(("extra","true"))
+  post_data += [('input[]', x) for x in peptides]
+  headers = {'Content-Type': 'application/x-www-form-urlencoded',  'Accept': 'application/json'}
+  url = 'http://api.unipept.ugent.be/api/v1/%s' % options.unipept
+  req = urllib2.Request( url, headers = headers, data = urllib.urlencode(post_data) )
+  resp = json.loads( urllib2.urlopen( req ).read() )
+  ## output results
+  if not (options.mismatch or options.json or options.tsv or options.csv):
+    print >> sys.stdout, str(resp)
+  if options.mismatch:
+    peptides_matched = []
+    for i,pdict in enumerate(resp):
+      peptides_matched.append(pdict['peptide'])
+    with open(options.mismatch,'w') as outputFile:
+      for peptide in peptides:
+        if not peptide in peptides_matched:
+          outputFile.write("%s\n" % peptide)
+  if options.json:
+    with open(options.json,'w') as outputFile:
+      outputFile.write(str(resp))  
+  if options.tsv or options.csv:
+    # 'pept2lca','pept2taxa','pept2prot'
+    pept2lca_column_order = [ 'peptide','superkingdom','kingdom','subkingdom','superphylum','phylum','subphylum','superclass','class_','subclass','infraclass','superorder','order','suborder','infraorder','parvorder','superfamily','family','subfamily','tribe','subtribe','genus','subgenus','species_group','species_subgroup','species','subspecies','varietas','forma' ]
+    pept2prot_column_order = [ 'peptide','uniprot_id','taxon_id','taxon_name','ec_references','go_references','refseq_ids','refseq_protein_ids','insdc_ids','insdc_protein_ids']
+    column_order = pept2prot_column_order if options.unipept == 'pept2prot' else pept2lca_column_order
+    found_keys = set()
+    results = []
+    for i,pdict in enumerate(resp):
+      results.append(pdict)
+      found_keys |= set(pdict.keys())
+      # print >> sys.stderr, "%s\n%s" % (pdict.keys(),found_keys)
+    column_names = []
+    column_keys = []
+    for col in column_order:
+      if col in found_keys:
+        column_names.append(col)
+        column_keys.append(col)
+      elif options.extra or options.names:
+        col_id = col+'_id'
+        col_name = col+'_name'
+        if options.extra:
+          if col_id in found_keys:
+            column_names.append(col_id)
+            column_keys.append(col_id)
+        if options.names:
+          if col_name in found_keys:
+            column_names.append(col)
+            column_keys.append(col_name)
+      else:
+        if col+'_name' in found_keys:
+          column_names.append(col)
+          column_keys.append(col+'_name')
+        elif col+'_id' in found_keys:
+          column_names.append(col)
+          column_keys.append(col+'_id')
+    # print >> sys.stderr, "%s\n%s" % (column_names,column_keys)
+    taxa = []
+    for i,pdict in enumerate(results):
+      vals = [str(pdict[x]) if x in pdict and pdict[x] else '' for x in column_keys]
+      taxa.append(vals)
+    if options.tsv:
+      with open(options.tsv,'w') as outputFile:
+        outputFile.write("#%s\n"% '\t'.join(column_names))
+        for vals in taxa:
+          outputFile.write("%s\n"% '\t'.join(vals))
+    if options.csv:
+      with open(options.csv,'w') as outputFile:
+        outputFile.write("%s\n"% ','.join(column_names))
+        for vals in taxa:
+          outputFile.write("%s\n"% ','.join(['"%s"' % (v if v else '') for v in vals]))
+
+if __name__ == "__main__" : __main__()