# HG changeset patch # User bornea # Date 1472866890 14400 # Node ID 43b9bad147df8fbb9030fcc85abdd08f81b57672 # Parent 792056ff8ed5dc5eae5c25b5f5715bbbdab682f9 Uploaded diff -r 792056ff8ed5 -r 43b9bad147df Protein_report_processing.py --- a/Protein_report_processing.py Fri Sep 02 16:32:26 2016 -0400 +++ b/Protein_report_processing.py Fri Sep 02 21:41:30 2016 -0400 @@ -0,0 +1,222 @@ +import sys +import os +from time import sleep + +files = sys.argv[1] # read in a string of file names seperated by ", " +# e.g. "Default_Protein_Report.txt, Default_Protein_Report_2.txt" +#bait = sys.argv[2] # SAINT formatted bait file +# still need a way to match files to bait identifiers +# or they can just be required to be put in the order of the bait file +quant_type = sys.argv[3] # what metric to use for quantification +# "#Validated Peptides", "#Peptides", "#Unique", "#Validated PSMs", "#PSMs" +db = sys.argv[4] # fasta database used in SearchGUI and PeptideShaker +prey = sys.argv[5] +tool_path = sys.argv[7] +if db == "None": + db = str(tool_path) + "/SwissProt_HUMAN_2015_12.fasta" +make_bait = sys.argv[6] +bait_bool = sys.argv[8] + +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" + bait_cache.append(str(bait_line)) + i = i + 3 + + for cache_line in bait_cache: + bait_file_tmp.write(cache_line) + + bait_file_tmp.close() + +if bait_bool == 'false': + bait_create(make_bait, infile) + bait = "bait.txt" +else: + bait_temp_file = open(sys.argv[9], 'r') + bait_cache = bait_temp_file.readlines() + bait_file_tmp = open("bait.txt", "wr") + for cache_line in bait_cache: + bait_file_tmp.write(cache_line) + bait_file_tmp.close() + bait = "bait.txt" + +class ReturnValue1(object): + def __init__(self, sequence, gene): + self.seqlength = sequence + self.genename = gene + +def read_tab(infile): + with open(infile,'r') as x: + output = [] + for line in x: + line = line.strip() + temp = line.split('\t') + output.append(temp) + return output +def printProgress (iteration, total, prefix = '', suffix = '', decimals = 1, barLength = 100): + """ + Call in a loop to create terminal progress bar + @params: + iteration - Required : current iteration (Int) + total - Required : total iterations (Int) + prefix - Optional : prefix string (Str) + suffix - Optional : suffix string (Str) + decimals - Optional : positive number of decimals in percent complete (Int) + barLength - Optional : character length of bar (Int) + """ + formatStr = "{0:." + str(decimals) + "f}" + percents = formatStr.format(100 * (iteration / float(total))) + filledLength = int(round(barLength * iteration / float(total))) + bar = '=' * filledLength + '-' * (barLength - filledLength) + sys.stdout.write('\r%s |%s| %s%s %s' % (prefix, bar, percents, '%', suffix)), + sys.stdout.flush() + if iteration == total: + sys.stdout.write('\n') + sys.stdout.flush() +def get_info(uniprot_accession_in,fasta_db): + # 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 + last_line = data_lines[-1] + 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_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()) + if data_lines[match] == last_line: + break + match = match + 1 + else: + break + return ReturnValue1(seqlength, genename) + if 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 data_lines[match]: + if match <= db_len: + seqlength = seqlength + len(data_lines[match].strip()) + if data_lines[match] == last_line: + break + 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 concatenate_files(file_list_string, bait_file): + file_list = file_list_string.split(",") + bait = read_tab(bait_file) + master_table = [] + header_check = 0 + file_cnt = 0 + table_cnt = 0 + for i in file_list: + table = read_tab(i) + for j in table: + if table_cnt == 0: + if header_check == 0: + header_check +=1 + j.append("Replicate") + j.append("Bait_Grouping") + master_table.append(j) + if table_cnt > 0: + j.append(bait[file_cnt][0]) + j.append(bait[file_cnt][1]) + master_table.append(j) + table_cnt +=1 + file_cnt+=1 + table_cnt = 0 + if len(master_table[0]) < len(master_table[1]): + master_table[0] = ["#"] + master_table[0] + with open("merged_PeptideShaker.txt","w") as x: + for i in master_table: + x.write("\t".join(i)) + x.write("\n") + return master_table +def make_inter(master_table,quant_type): + if len(master_table[0]) < len(master_table[1]): + master_table[0] = ["#"] + master_table[0] + replicate_index = master_table[0].index("Replicate") + grouping_index = master_table[0].index("Bait_Grouping") + accession_index = master_table[0].index("Main Accession") + quant_type = quant_type.replace("_", " ") + quant_type = r"#" + quant_type + Quant_index = master_table[0].index(quant_type) + inter_file = "" + for i in master_table[1:]: + line = [] + line.append(i[replicate_index]) + line.append(i[grouping_index]) + line.append(i[accession_index]) + line.append(i[Quant_index]) + inter_file = inter_file + "\t".join(line) + "\n" + with open("inter.txt","w") as x: + x.write(inter_file) + +def make_prey(concat_table,fasta_db): + input_data = concat_table + if len(input_data[0]) < len(input_data[1]): + input_data[0] = ["#"] + input_data[0] + accession_index = input_data[0].index("Main Accession") + proteins = [] + for i in input_data[1:]: + if i[accession_index] not in proteins: + proteins.append(i[accession_index]) + output_file = open("prey.txt", 'w') + start = 0 + end = len(proteins) + + # Initial call to print 0% progress + printProgress(start, end, prefix = 'Progress:', suffix = 'Complete', barLength = 50) + + for protein in proteins: + seq = get_info(protein,fasta_db).seqlength + GN = get_info(protein,fasta_db).genename + if seq != 'NA': + output_file.write(protein + "\t" + str(seq) + "\t" + str(GN) + "\n") + start+=1 + printProgress(start, end, prefix = 'Progress:', suffix = 'Complete', barLength = 50) + output_file.close() +data = concatenate_files(files,bait) +make_inter(data, quant_type) +if prey == "true": + make_prey(data,db) + +os.rename("bait.txt", sys.argv[2]) +os.rename("inter.txt", sys.argv[10]) +if str(prey) != "None": + os.rename("prey.txt", sys.argv[11]) \ No newline at end of file