# HG changeset patch # User bornea # Date 1454089947 18000 # Node ID fd27366b9faf6bcd12e84d3ab18094928adcea5a # Parent f8ef6b24862ba423e431dae3bef3b9faa089753e Uploaded diff -r f8ef6b24862b -r fd27366b9faf ProteinInteractions_v2.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/ProteinInteractions_v2.py Fri Jan 29 12:52:27 2016 -0500 @@ -0,0 +1,208 @@ +################################################################################ +# This program will read in a SAINT 'list.txt' file and the interactions from +# the consensus path db database and return all the interactions that we saw in +# our experiment in a format suitable for cytoscape. This allows us to filter +# before getting PPIs so that it doesn't affect our SAINT score or include +# interactions that don't score well +################################################################################ +# Copyright (C) Brent Kuenzi. +# Permission is granted to copy, distribute and/or modify this document +# under the terms of the GNU Free Documentation License, Version 1.3 +# or any later version published by the Free Software Foundation; +# with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. +# A copy of the license is included in the section entitled "GNU +# Free Documentation License". +################################################################################ +## REQUIRED INPUT ## + +# 1) listfile: SAINTexpress output +# 2) SAINT_cutoff: Saint score cutoff for import (between 0 and 1) +# 3) Int_conf: Confidence of PPI from CPDB to include +# - low: no filtering +# - medium: >0.5 +# - high: >0.7 +# - very high: >0.9 +# 4) Species: Human, Yeast, or Mouse +################################################################################ + + +import urllib2 +import itertools +import sys +import os + + +listfile = sys.argv[1] +SAINT_cutoff = sys.argv[2] +Int_conf = sys.argv[3] +Species = sys.argv[4] +cyto_file = sys.argv[5] +db_path = sys.argv[6] + + +class ReturnValue1(object): + def __init__(self, uniprot_acc, gene, swissprot): + self.up = uniprot_acc + self.gn = gene + self.sp = swissprot +class ReturnValue2(object): + def __init__(self, getdata, getproteins, getheader): + self.data = getdata + self.proteins = getproteins + self.header = getheader + + +def main(listfile, SAINT_cutoff, Int_conf, Species): + cytoscape(dd_network(listfile, SAINT_cutoff, Int_conf), listfile, SAINT_cutoff) + + +def readtab(infile): + with open(infile, 'r') as file_to_read: + # Read in tab-delim text. + output = [] + for line in file_to_read: + line = line.strip() + temp = line.split('\t') + output.append(temp) + return output + + +def read_listfile(listfile): + # Get data, proteins and header from scaffold output + dupes = readtab(listfile) + header = dupes[0] + prot_start = header.index("PreyGene")-1 + data = dupes[1:] + # Cut off blank line and END OF FILE. + proteins = [] + for protein in data: + proteins.append(protein[prot_start]) + return ReturnValue2(data, proteins, header) + + +def get_info(uniprot_accession_in): + # Get aa lengths and gene name. + error = open('error proteins.txt', 'a+') + i = 0 + while i == 0: + try: + data = urllib2.urlopen("http://www.uniprot.org/uniprot/" + uniprot_accession_in + + ".fasta") + break + except urllib2.HTTPError, err: + i = i + 1 + if i == 50: + sys.exit("More than 50 errors. Check your file or try again later.") + if err.code == 404: + error.write(uniprot_accession_in + '\t' + "Invalid URL. Check protein" + '\n') + seqlength = 'NA' + genename = 'NA' + return ReturnValue1(seqlength, genename) + elif err.code == 302: + sys.exit("Request timed out. Check connection and try again.") + else: + sys.exit("Uniprot had some other error") + lines = data.readlines() + header = lines[0] + lst = header.split('|') + lst2 = lst[2].split(' ') + swissprot = lst2[0] + uniprot_acc = lst[1] + if lines == []: + error.write(uniprot_accession_in + '\t' + "Blank Fasta" + '\n') + error.close + uniprot_acc = 'NA' + genename = 'NA' + return ReturnValue1(uniprot_acc, genename, swissprot) + if lines != []: + seqlength = 0 + header = lines[0] + if 'GN=' in header: + lst = header.split('GN=') + lst2 = lst[1].split(' ') + genename = lst2[0] + error.close + return ReturnValue1(uniprot_acc, genename, swissprot) + if 'GN=' not in header: + genename = 'NA' + error.close + return ReturnValue1(uniprot_acc, genename, swissprot) + + +def dd_network(listfile, SAINTscore, CPDB_filter): + # Filter by SS and CPDB. + data = read_listfile(listfile).data + # Change to filtered list. + SS = (read_listfile(listfile).header).index("SaintScore") + filt_data = [] + for i in data: + if i[SS] >= SAINTscore: + filt_data.append(i) + accessions = [] + for i in filt_data: + accessions.append(get_info(i[1]).sp) + GO = [] + for i in CPDB[2:]: + if i[3] >= CPDB_filter: + # Filter interaction confidence. + GO.append(i[2]) + # All known interactions. + GO2 = [] + for i in GO: + GO2.append(i.split(',')) + # Make interactions list friendly. + unfiltered_network = {} + for i in accessions: + interactions = [] + for j in GO2: + if i in j: + # Find the interactions. + if j not in interactions: + # Dont add duplicate interactions. + interactions.append(j) + merged = list(itertools.chain(*interactions)) + # Flatten list of lists. + unfiltered_network[i] = merged + # Assign all possible interactions to protein in a dictionary. + dd_network = {} + # Data dependent network. + for i in unfiltered_network: + temp = [] + for j in unfiltered_network[i]: + if j in accessions: + if j not in temp: + if j != i: + temp.append(j) + dd_network[i] = temp + return dd_network + + +def cytoscape(dd_network, listfile, SAINTscore): + with open('network.sif', 'wt') as y: + data = read_listfile(listfile).data + SS = (read_listfile(listfile).header).index("SaintScore") + filt_data = [] + for i in data: + if i[SS] >= SAINTscore: + filt_data.append(i) + header = ["Prey", "Interactions"] + header = '\t'.join(header) + y.write(header + '\n') + for i in filt_data: + if dd_network[i[1]] != []: + lst = [] + for j in dd_network[i[1]]: + lst.append(j) + for j in lst: + y.write(i[1]+'\t'+'pp'+'\t' + j+'\n') + + +if Species == "Human": + CPDB = readtab(str(db_path) + 'ConsensusPathDB_human_PPI.txt') +if Species == "Yeast": + CPDB = readtab(str(db_path) + 'ConsensusPathDB_yeast_PPI.txt') +if Species == "Mouse": + CPDB = readtab(str(db_path) +'ConsensusPathDB_mouse_PPI.txt') +if __name__ == '__main__': + main(listfile, SAINT_cutoff, Int_conf, Species) + os.rename('network.sif', str(cyto_file))