FimoEvaluator_P53.py

#!/usr/bin/python

import sys
import getopt
from CandidateSequences_P53 import CandidateSequences


motif_family = ["P53","TP53","P73"]
#main runtime, passes in the FIMO result pipe from shell script
#overall idea is to process the entries and sort them as them come in.
class Usage(Exception):
  def __init__(self, msg):
    self.msg = msg


if __name__ == "__main__":
  sys.exit(main())
  
def main(argv=None):
  if argv is None:
    argv = sys.argv
  try:
    
    try:
      opts, args = getopt.getopt(argv[1:],"h",["help","motiffam=","collection="])
      for o, a in opts:
        if o in ("--motiffam"):
          motif_family = a
        elif o in ("--collection"):
          collection_base_name = a
    except getopt.error,msg:
      raise Usage(msg)
  
  except Usage, err:
    print >>sys.stderr, err.msg
    print >>sys.stderr, "for help use --help"
    return 2

  result_list = []
  #instead of a pure dict, instantiate a object that holds a dict and contains a
  #number of methods
  sequence_container = CandidateSequences()
  for place,line in enumerate(sys.stdin):
    #skip the first line
    if place:
      #create a dict, store entries in the dict
      #pass in old dict into function and line, 
      #pdb.set_trace()
      is_valid = sequence_container.add_entry(line)
      #function parses line, and appends entry to the key
      result_list.append(line)

  #after the results are aggregated, perform calculations
  sequence_container.calculate_senspec(motif_family)
  #insert to model
  #sequence_container.insert_contents(Model)
  sequence_container.insert_contents(collection_base_name)

  #big_dict = sequence_container.get_dict()
  #with open('testing.txt','w') as testfile:
    #for key in big_dict:
      #testfile.write(key + '\n')
    #testfile.write("".join(result_list))

#write parseline helper function that belongs to dict object

#write parse line exceptions function that removes '+' strand
#write/create dict object that stores keys
#insert entries and return summary count


#when all insertion is done:

#summarize results from FIMO file. get sequence score
#get on target and off target motifs
#calculate sensitivity and specificity, return that information or store it?
#these methods should be stored in the FIMOData object
#access functions, getScores, getBlah

#finally, insert database into mongo

#should I write a model wrapper? nah its okay for now
#use pymongo as a model wrapper
#insert summarized batch into mongodb database