msqrob_parser_MD.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
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    "variable_ptm_dict = {\n",
    "    \"K\": {\n",
    "        \"Ac\": \"ac\",\n",
    "        \"Bu\": \"me\",\n",
    "        \"Me2\": \"me2\",\n",
    "        \"Me3\": \"me3\",\n",
    "        \"Cr\": \"cr\",\n",
    "        \"Hib\": \"hib\",\n",
    "        \"Su\": \"su\"\n",
    "    },\n",
    "    \"R\": {\n",
    "        \"Me\": \"me\",\n",
    "        \"Me2\": \"me2\",\n",
    "        \"Cit\": \"cit\",\n",
    "    },\n",
    "    \"M\": {\n",
    "        \"Ox\": \"ox\",\n",
    "    },\n",
    "}\n",
    "unmodified_abbreviation = \"un\"\n",
    "\n",
    "fasta_file_name = \"/mnt/d/MSqRob/hPTM_Parsing/Test cases/FASTA/HumanMycoCrap_2018_nr.fasta\"\n",
    "progenesis_file_name = \"/mnt/d/MSqRob/hPTM_Parsing/Test cases/hPTMs/All_Peptide_IDs_For_MSqRob_RawAbundance.csv\"\n",
    "out_file_name = progenesis_file_name[:-4] + \"_SW.csv\"\n",
    "verbose = False\n",
    "\n",
    "def ptm_format(raw_ptm):\n",
    "    loc, aa, *ptm = raw_ptm.split()\n",
    "    ptm = \" \".join(ptm)\n",
    "    return loc, ptm, aa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "variable_ptm_dict = {\n",
    "    \"K\": {\n",
    "        \"Dimethyl\": \"me2\",\n",
    "        \"Trimethyl\": \"me3\",\n",
    "        \"EG 2-Hydroxyisobutyrylation\": \"hib\",\n",
    "    },\n",
    "    \"R\": {\n",
    "        \"Dimethyl\": \"me2\",\n",
    "        \"EG Citrullination\": \"cit\",\n",
    "    },\n",
    "}\n",
    "unmodified_abbreviation = \"un\"\n",
    "\n",
    "fasta_file_name = \"/home/sander/Documents/Proteomics/msqrob/data/HumanMycoCrap_2018_nr.fasta\"\n",
    "progenesis_file_name = \"/home/sander/Documents/Proteomics/msqrob/data/Novel_Export_ForSW_Parsing.csv\"\n",
    "out_file_name = progenesis_file_name[:-4] + \"_SW.csv\"\n",
    "verbose = True\n",
    "\n",
    "def ptm_format(raw_ptm):\n",
    "    loc, *ptm, aa = raw_ptm.split()\n",
    "    ptm = \" \".join(ptm)\n",
    "    return loc, ptm, aa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pyteomics\n",
    "from pyteomics import fasta\n",
    "import csv\n",
    "\n",
    "description_format=lambda x: x.split()[0].split(\"|\")[-1]\n",
    "protein_sequences = {description_format(description): sequence for description, sequence in pyteomics.fasta.read(fasta_file_name)}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def parsePTMs(ptm_string, peptide_sequence, peptide_start_index, verbose=False):\n",
    "    ptms = {\n",
    "        \"{}{}\".format(\n",
    "            aa,\n",
    "            peptide_start_index + index + 1\n",
    "        ): unmodified_abbreviation for index, aa in enumerate(\n",
    "            peptide_sequence\n",
    "        ) if aa in variable_ptm_dict\n",
    "    }\n",
    "    if len(ptm_string) > 0:\n",
    "        for raw_ptm in ptm_string.split(\"|\"):\n",
    "#             if \"ropion\" in raw_ptm:\n",
    "#                 continue\n",
    "            try:\n",
    "                loc, ptm, aa = ptm_format(raw_ptm)\n",
    "            except ValueError:\n",
    "                if verbose:\n",
    "                    print(\n",
    "                        \"Undefined ptm {} on peptide {}\".format(raw_ptm, peptide_sequence)\n",
    "                    )\n",
    "                raise Error\n",
    "                continue    \n",
    "            try:\n",
    "                loc = int(loc[1: -1])\n",
    "            except ValueError:\n",
    "                if verbose:\n",
    "                    print(\n",
    "                        \"Undefined ptm {} on peptide {}\".format(raw_ptm, peptide_sequence)\n",
    "                    )\n",
    "                continue\n",
    "            aa = aa[1: -1]\n",
    "            format_string = \"{}{}\".format(aa, peptide_start_index + loc)\n",
    "            if format_string not in ptms:\n",
    "                if verbose:\n",
    "                    print(\n",
    "                        \"Undefined ptm {} on peptide {}\".format(raw_ptm, peptide_sequence)\n",
    "                    )\n",
    "                continue\n",
    "            try:\n",
    "                ptms[format_string] = variable_ptm_dict[aa][ptm]\n",
    "            except KeyError:\n",
    "                if verbose:\n",
    "                    print(\n",
    "                        \"Undefined ptm {} on peptide {}\".format(raw_ptm, peptide_sequence)\n",
    "                    )\n",
    "                continue\n",
    "    return [\"{}{}\".format(aa_loc, ptm) for aa_loc, ptm in ptms.items()]\n",
    "\n",
    "with open(progenesis_file_name, \"r\") as raw_infile:\n",
    "    header = True\n",
    "    infile = csv.reader(raw_infile)\n",
    "    with open(out_file_name, \"w\") as raw_outfile:\n",
    "        outfile = csv.writer(raw_outfile)\n",
    "        for row in infile:\n",
    "            row_addition = \"\"\n",
    "            if header:\n",
    "                if \"Sequence\" in row:\n",
    "                    header = False\n",
    "                    sequence_column_index = row.index(\"Sequence\")\n",
    "                    protein_column_index = row.index(\"Protein\")\n",
    "                    ptm_column_index = row.index(\"Variable modifications ([position] description)\")\n",
    "                    row_addition = \"msqrob_proteins\"\n",
    "                outfile.writerow(row + [row_addition])\n",
    "            else:\n",
    "                peptide_sequence = row[sequence_column_index]\n",
    "                proteins_string = row[protein_column_index]\n",
    "                ptm_string = row[ptm_column_index]\n",
    "                if proteins_string != \"\":\n",
    "                    row_additions = []\n",
    "                    for protein_id in proteins_string.split(\";\"):\n",
    "                        peptide_start_index = protein_sequences[protein_id].index(peptide_sequence)\n",
    "                        peptide_end_index = peptide_start_index + len(peptide_sequence)\n",
    "                        ptms = parsePTMs(ptm_string, peptide_sequence, peptide_start_index, verbose)\n",
    "                        for ptm in ptms:\n",
    "                            row_addition =  \"{}_{}-{}_{}\".format(\n",
    "                                protein_id,\n",
    "                                peptide_start_index, \n",
    "                                peptide_end_index,\n",
    "                                ptm\n",
    "                            )\n",
    "                            outfile.writerow(row + [row_addition])\n",
    "#                         row_additions += [\n",
    "#                             \"{}_{}-{}_{}\".format(\n",
    "#                                 protein_id,\n",
    "#                                 peptide_start_index, \n",
    "#                                 peptide_end_index,\n",
    "#                                 ptm\n",
    "#                             ) for ptm in ptms\n",
    "#                         ]\n",
    "#                     row_addition = \";\".join(row_additions)\n",
    "                else:\n",
    "                    outfile.writerow(row + [row_addition])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "cell_type": "code",
   "execution_count": null,
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