diff SAINT_preprocessing_v6_mq_pep.py @ 28:5be5c9c81bda draft

Uploaded

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/SAINT_preprocessing_v6_mq_pep.py	Thu Jan 28 13:53:14 2016 -0500
@@ -0,0 +1,268 @@
+#######################################################################################
+# Python-code: SAINT pre-processing from MaxQuant "Samples Report" output
+# Author: Brent Kuenzi
+#######################################################################################
+# This program reads in a raw MaxQuant "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: MaxQuant "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
+
+
+mq_file = sys.argv[1]
+ins_path = sys.argv[8]
+names_path = str(ins_path) + r"uniprot_names.txt"
+cmd = (r"Rscript "+ str(ins_path) +"pre_process_protein_name_set.R " + str(mq_file) +
+       " " + str(names_path))
+os.system(cmd)
+
+infile = "./tukeys_output.txt" 
+# The MaxQuant "Samples Report" output.
+prey = sys.argv[2] 
+# Y or N boolean from Galaxy.
+fasta_db = sys.argv[3]
+if fasta_db == "None":
+    fasta_db = str(ins_path)  + "SwissProt_HUMAN_2014_08.fasta"
+make_bait = sys.argv[6]
+bait_bool = sys.argv[9]
+
+def bait_create(baits, infile):
+    # Takes the Bait specified by the user and makes them into a Bait file and includes a
+    # check to make sure they are using valid baits.
+    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.replace("\"", "")
+            input_line = input_line.replace(r"Intensity.", "")
+            # R coerces "-" into "." changes them back and remove Intensity from the Bait names.
+            input_line = input_line.replace(r".", r"-")
+            temp = input_line.split()
+            if "mapped_protein" 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
+    # Writes cache to Bait file.
+    bait_cache.sort()
+    for line in bait_cache:
+        bait_file_tmp.write(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()
+    bait_file_tmp = open("bait.txt", "wr")
+    for line in bait_cache:
+        bait_file_tmp.write(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(MaxQuant_input, make_bait):
+    #bait_check(baitfile, MaxQuant_input)
+    make_inter(MaxQuant_input)
+    if prey == 'true':
+        make_prey(MaxQuant_input)
+        no_error_inter(MaxQuant_input)
+        os.rename('prey.txt', sys.argv[5])
+    elif prey == 'false':
+        if os.path.isfile('error proteins.txt') == True:
+            no_error_inter(MaxQuant_input)
+        pass
+    elif prey != 'true' or 'false':
+        sys.exit("Invalid Prey Argument: Y or N")
+    os.rename('inter.txt', sys.argv[4])
+    os.rename("bait.txt", sys.argv[7])
+
+
+def get_info(uniprot_accession_in): 
+    # Get aa 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:
+            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())
+                        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 file.
+        output = []
+        for input_line in input_file:
+            input_line = input_line.strip()
+            temp = input_line.split('\t')
+            output.append(temp)
+    return output
+
+
+def read_MaxQuant(MaxQuant_input):
+    # Get data, proteins and header from MaxQuant output.
+    dupes = readtab(MaxQuant_input)
+    header_start = 0
+    header = dupes[header_start]
+    for var_MQ in header:
+        var_MQ = var_MQ.replace(r"\"", "")
+        var_MQ = var_MQ.replace(r"Intensity.", r"")
+        var_MQ = var_MQ.replace(r".", r"-")
+    data = dupes[header_start+1:len(dupes)]
+    # Cut off blank line and END OF FILE.
+    proteins = []
+    for protein in data:
+        proteins.append(protein[0])
+    return ReturnValue2(data, proteins, header)
+
+
+def make_inter(MaxQuant_input):
+    bait = readtab(baitfile)
+    data = read_MaxQuant(MaxQuant_input).data
+    header = read_MaxQuant(MaxQuant_input).header
+    proteins = read_MaxQuant(MaxQuant_input).proteins
+    bait_index = []
+    for bait_item in bait:
+        bait_index.append(header.index("mapped_protein") + 1)
+        # Find just the baits defined in bait file.
+    with open('inter.txt', 'w') as y:
+        a = 0; l = 0
+        for bb in bait:
+            for lst in data:
+                y.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(MaxQuant_input):
+    proteins = read_MaxQuant(MaxQuant_input).proteins
+    output_file = open("prey.txt", 'w')
+    for a in proteins:
+        a = a.replace("\n", "")
+        # Remove \n for input into function.
+        a = a.replace("\r", "")
+        # Ditto for \r.
+        seq = get_info(a).seqlength
+        GN = get_info(a).genename
+        if seq != 'NA':
+            output_file.write(a+"\t"+str(seq)+ "\t" + str(GN) + "\n")
+    output_file.close()
+
+
+def no_error_inter(MaxQuant_input):
+    # Remake inter file without protein errors from Uniprot.
+    err = readtab("error proteins.txt")
+    bait = readtab(baitfile)
+    data = read_MaxQuant(MaxQuant_input).data
+    header = read_MaxQuant(MaxQuant_input).header
+    header = [MQ_var.replace(r"\"", "") for MQ_var in header]
+    header = [MQ_var.replace(r"Intensity.", r"") for MQ_var in header]
+    header = [MQ_var.replace(r".", r"-") for MQ_var in header]
+    bait_index = []
+    for bait_item in bait:
+        bait_index.append(header.index(bait_item[0]))
+    proteins = read_MaxQuant(MaxQuant_input).proteins
+    errors = []
+    for e in err:
+        errors.append(e[0])
+    with open('inter.txt', 'w') as input_file:
+        l = 0; a = 0
+        for bb in bait:
+            for lst in data:
+                if proteins[a] not in errors:
+                    input_file.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, MaxQuant_input):
+    # Check that bait names share header titles.
+    bait_in = readtab(bait)
+    header = read_MaxQuant(MaxQuant_input).header
+    for bait in bait_in:
+        if bait[0] not in header:
+            sys.exit("Bait must share header titles with MaxQuant output")
+
+if __name__ == '__main__':
+    main(infile, make_bait)