Mercurial > repos > bornea > query_crapome
view CRAPomeQuery.py @ 6:fccd12a1ffe8 draft
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author | bornea |
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date | Mon, 18 Apr 2016 12:19:04 -0400 |
parents | d1a26feef9de |
children | 6fe48eb42c55 |
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# -*- coding: utf-8 -*- """ Created on Thu Apr 14 16:58:05 2016 @author: brentkuenzi """ ################################################################################ # This program will read in a SAINT formatted 'prey.txt' file or a file # containing a single column list of uniprot accessions (e.g. "P00533" or # "EGFR_HUMAN")query the CRAPome database (v1.1), and return a file specifying # the prevalence of each protein in the CRAPome. ################################################################################ # 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) crappyData: Prey.txt or single column list of Uniprot accessions crappyData = sys.argv[1] # Prey file or File with single column of accessions # 2) Species: HUMAN or YEAST species = sys.argv[2] # HUMAN or YEAST db_path = sys.argv[4] ################################################################################ ## Dependencies ## import urllib2 import sys import numpy import os ################################################################################ ## Global Variables ## if species == "HUMAN": database = str(db_path) + "Human_CRAPome_v1-1.txt" if species == "YEAST": database = str(db_path) + "Yeast_CRAPome_v1-1.txt" ################################################################################ ## CRAPomeQuery ## class ReturnValue1(object): def __init__(self, uniprot_acc, gene, swissprot): self.up = uniprot_acc self.gn = gene self.sp = swissprot 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 readtab(infile): # read in tab-delim text with open(infile,'r') as x: output = [] for line in x: line = line.strip() temp = line.split('\t') output.append(temp) return output def crapome(infile): # Query CRAPome data = readtab(infile) crapome = readtab(database) filt = [] for i in data: # Filter CRAPome database on our data flag = 0 # is protein in CRAPome? ac_flag = 0 # is it _SPECIES or not unique = 0 # only take first ID in CRAPome if "_"+species in i[0]: ac = i[0] else: ac = get_info(i[0]).sp # query swissprot if not _SPECIES ac_flag +=1 for j in crapome: if ac == j[2]: if ac_flag == 0: # if _SPECIES if unique == 0: filt.append(j) flag+=1 unique+=1 if ac_flag != 0: # if not _SPECIES if unique == 0: unique+=1 j[2] = i[0] # change to user input filt.append(j) flag +=1 if flag == 0: # if protein is not present in CRAPome database then add it filt.append(["\t", "\t", i[0], "Invalid identifier / gene not available"]) total = 0 # Experiment counter query = [] for i in filt: # Create CRAPome file as list temp=[] if len(i) > 5: cnt=0 temp.append(i[2]) # append accession temp.append(i[0]) # append gene name ave = [] total = len(i[3:]) # calculate total experiments for j in i[3:]: if j != '0': ave.append(int(j)) # calculate Ave.SC on only experiments with ID cnt+=1 temp.append(str(cnt) + " / "+str(total)) # format ratio if ave != []: temp.append(str(round(numpy.mean(ave),1))) # calculate Ave.SC temp.append(str(max(ave))) # calculate Max.SC else: temp.append(0) # add 0 if has not been ID'd in CRAPome temp.append(0) # add 0 if has not been ID'd in CRAPome else: temp.append(i[2]) # append accession temp.append(i[3]) query.append(temp) # final query results header = ["User Input","Mapped Gene Symbol","Num of Expt. (found/total)","Ave SC","Max SC"] with open("Crappy Data.txt","wt") as x: # write file x.write("\t".join(header) + "\n") for i in query: x.write("\t".join(i) + "\n") if __name__ == '__main__': crapome(crappyData) os.rename("Crappy Data.txt", sys.argv[3]) ## END ##