Update 2-24-15

Inputs: fasta files, parameters
Outputs: top motifs, visualization of GC skew across sequence
Programs: Python and R (or just Python).

Very raw pseudocode for motif finding:


wf = open(top_motifs.txt, w)

seq = "store input file into a string"

user input for window and slide size = input("some message:" usr_input)

window_size = usr_input
slide_size = usr_input


motifs = {}


for window in seq:
      if not previously stored motif:
           unk_motif = "unk_motif"
           motifs[unk_motif] = 1
      elif:
           update dict value + 1 to preexisting motif
           motifs[
      else:
           break loop when window reaches the end of seq


if top_motifs.txt.closed == False:
      top_motifs.txt.closed()

I realize I need to find a method for building a dictionary on the fly while also updating values to reoccurring keys. Also, I am thinking that I should also keep track of motif position as some sort of metadata that can be called with an option when running the program. Calculating GC skew will use a similar method of a sliding window however, I still do not know how to generate figures in python.