Mercurial > repos > bornea > saint_preproc
view SAINT_preprocessing_v6.py @ 32:fce21ee45396 draft
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author | bornea |
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date | Thu, 28 Jan 2016 13:54:09 -0500 |
parents | 09612857d26a |
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####################################################################################### # Python-code: SAINT pre-processing from Scaffold "Samples Report" output # Author: Brent Kuenzi ####################################################################################### # This program reads in a raw Scaffold "Samples Report" output and a user generated # bait file and autoformats it into prey and interaction files for SAINTexpress # analysis ####################################################################################### # 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) infile: Scaffold "Samples Report" output # 2) baitfile: SAINT formatted bait file generated in Galaxy # 3) fasta_db: fasta database for use (defaults to SwissProt_HUMAN_2014_08.fasta) # 4) prey: Y or N for generating a prey file # 5) make_bait: String of bait names, assignment, and test or control boolean ####################################################################################### import sys import os.path infile = sys.argv[1] #Scaffold "Samples Report" output. prey = sys.argv[2] # Y or N boolean from Galaxy. fasta_db = sys.argv[3] tool_path = sys.argv[8] if fasta_db == "None": fasta_db = str(tool_path) + "/SwissProt_HUMAN_2014_08.fasta" make_bait = sys.argv[6] bait_bool = sys.argv[9] def bait_create(baits, infile): # Verifies the Baits are valid in the Scaffold file and writes the Bait.txt. baits = make_bait.split() i = 0 bait_file_tmp = open("bait.txt", "w") order = [] bait_cache = [] while i < len(baits): if baits[i+2] == "true": T_C = "C" else: T_C = "T" bait_line = baits[i] + "\t" + baits[i+1] + "\t" + T_C + "\n" read_infile = open(infile, "r") for input_line in read_infile: input_line = input_line.strip() temp = input_line.split('\t') if "Quantitative Variance" in str(temp): if baits[i] in temp: number_bait = temp.index(str(baits[i])) number_bait = number_bait - 9 bait_cache.append((number_bait, str(bait_line))) # Locates the Bait names in the column names and then sets the Baits in the # correct order in the cache thus the - 9 because the baits start at the 9th # column. else: print "Error: bad bait " + str(baits[i]) sys.exit() else: pass i = i + 3 bait_cache.sort() for cache_line in bait_cache: bait_file_tmp.write(cache_line[1]) bait_file_tmp.close() if bait_bool == 'false': bait_create(make_bait, infile) baitfile = "bait.txt" else: bait_temp_file = open(sys.argv[10], 'r') bait_cache = bait_temp_file.readlines() print bait_cache bait_file_tmp = open("bait.txt", "wr") for cache_line in bait_cache: bait_file_tmp.write(cache_line) bait_file_tmp.close() baitfile = "bait.txt" class ReturnValue1(object): def __init__(self, sequence, gene): self.seqlength = sequence self.genename = gene class ReturnValue2(object): def __init__(self, getdata, getproteins, getheader): self.data = getdata self.proteins = getproteins self.header = getheader def main(Scaffold_input, baits): bait_check(baitfile, Scaffold_input) make_inter(Scaffold_input) if prey == 'true': make_prey(Scaffold_input) no_error_inter(Scaffold_input) os.rename('prey.txt', sys.argv[5]) elif prey == 'false': if os.path.isfile('error proteins.txt') == True: no_error_inter(Scaffold_input) pass elif prey != 'true' or 'false': sys.exit("Invalid Prey Argument: Y or N") def get_info(uniprot_accession_in): # Get aminoacid lengths and gene name. error = open('error proteins.txt', 'a+') data = open(fasta_db, 'r') data_lines = data.readlines() db_len = len(data_lines) seqlength = 0 count = 0 for data_line in data_lines: if ">sp" in data_line: namer = data_line.split("|")[2] if uniprot_accession_in == data_line.split("|")[1]: match = count + 1 if 'GN=' in data_line: lst = data_linedata_line.split('GN=') lst2 = lst[1].split(' ') genename = lst2[0] if 'GN=' not in data_line: genename = 'NA' while ">sp" not in data_lines[match]: if match <= db_len: seqlength = seqlength + len(data_lines[match].strip()) match = match + 1 else: break return ReturnValue1(seqlength, genename) elif uniprot_accession_in == namer.split(" ")[0]: match = count + 1 # Ensures consistent spacing throughout. if 'GN=' in data_line: lst = data_line.split('GN=') lst2 = lst[1].split(' ') genename = lst2[0] if 'GN=' not in data_line: genename = 'NA' while ">sp" not in lines[match]: if match <= db_len: seqlength = seqlength + len(lines[match].strip()) match = match + 1 else: break return ReturnValue1(seqlength, genename) count = count + 1 if seqlength == 0: error.write(uniprot_accession_in + '\t' + "Uniprot not in Fasta" + '\n') error.close seqlength = 'NA' genename = 'NA' return ReturnValue1(seqlength, genename) def readtab(infile): with open(infile, 'r') as input_file: # read in tab-delim text output = [] for input_line in input_file: input_line = input_line.strip() temp = input_line.split('\t') output.append(temp) return output def read_Scaffold(Scaffold_input): # Get data, proteins and header from Scaffold output dupes = readtab(Scaffold_input) cnt = 0 for Scaffold_line in dupes: cnt += 1 if Scaffold_line[0] == '#': # Finds the start of second header. header_start = cnt-1 header = dupes[header_start] prot_start = header.index("Accession Number") data = dupes[header_start+1:len(dupes)-2] # Cut off blank line and END OF FILE. proteins = [] for Scaffold_line in data: Scaffold_line[4] = Scaffold_line[4].split()[0] # Removes the (+##) that sometimes is attached. for protein in data: proteins.append(protein[prot_start]) return ReturnValue2(data, proteins, header) def make_inter(Scaffold_input): bait = readtab(baitfile) data = read_Scaffold(Scaffold_input).data header = read_Scaffold(Scaffold_input).header proteins = read_Scaffold(Scaffold_input).proteins bait_index = [] for bait_line in bait: bait_index.append(header.index(bait_line[0])) # Find just the baits defined in bait file. with open('inter.txt', 'w') as inter_file: a = 0; l = 0 for bb in bait: for lst in data: inter_file.write(header[bait_index[l]] + '\t' + bb[1] + '\t' + proteins[a] + '\t' + lst[bait_index[l]] + '\n') a += 1 if a == len(proteins): a = 0; l += 1 def make_prey(Scaffold_input): proteins = read_Scaffold(Scaffold_input).proteins output_file = open("prey.txt", 'w') for protein in proteins: protein = protein.replace("\n", "") # Remove \n for input into function. protein = protein.replace("\r", "") # Ditto for \r. seq = get_info(protein).seqlength GN = get_info(protein).genename if seq != 'NA': output_file.write(protein + "\t" + str(seq) + "\t" + str(GN) + "\n") output_file.close() def no_error_inter(Scaffold_input): # Remake inter file without protein errors from Uniprot. err = readtab("error proteins.txt") bait = readtab(baitfile) data = read_Scaffold(Scaffold_input).data header = read_Scaffold(Scaffold_input).header bait_index = [] for bait_line in bait: bait_index.append(header.index(bait_line[0])) proteins = read_Scaffold(Scaffold_input).proteins errors = [] for e in err: errors.append(e[0]) with open('inter.txt', 'w') as y: l = 0; a = 0 for bb in bait: for lst in data: if proteins[a] not in errors: y.write(header[bait_index[l]] + '\t' + bb[1] + '\t' + proteins[a] + '\t' + lst[bait_index[l]] + '\n') a += 1 if a == len(proteins): l += 1; a = 0 def bait_check(bait, Scaffold_input): # Check that bait names share Scaffold header titles. bait_in = readtab(bait) header = read_Scaffold(Scaffold_input).header for i in bait_in: if i[0] not in header: sys.exit("Bait must share header titles with Scaffold output") if __name__ == '__main__': main(infile, baitfile) os.rename("inter.txt", sys.argv[4]) os.rename("bait.txt", sys.argv[7])