Create_dataset_tsv.ipynb

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   "source": [
    "##### `If your files originate from a Thermo instrument:`\n",
    "\n",
    "Copy all your *.raw files to data/raw directory and you can use the following script to generate a samples.tsv file automatically:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9d2ea905",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os\n",
    "df = pd.DataFrame()\n",
    "df[\"sample_name\"] = [file for file in os.listdir(os.path.join(\"data\", \"raw\")) if file.endswith(\".raw\")]\n",
    "df[\"sample_name\"]=df[\"sample_name\"].replace(\".raw\", value=\"\", regex=True)\n",
    "df[\"comment\"] = \" \"\n",
    "df[\"MAPnumber\"] = \" \"\n",
    "df.to_csv(os.path.join(\"config\", \"dataset.tsv\"), sep=\"\\t\")\n",
    "df.to_csv(os.path.join(\"config\", \"samples.tsv\"), sep=\"\\t\")\n",
    "df"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "63b9b610",
   "metadata": {},
   "source": [
    "##### `If your files originate from another instrument:`\n",
    "\n",
    "Copy all your already converted files *.mzML to data/mzML directory and you can use the following script to generate a samples.tsv file automatically:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a81d0bbd",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os\n",
    "df = pd.DataFrame()\n",
    "df[\"sample_name\"] = [file for file in os.listdir(os.path.join(\"data\", \"mzML\")) if file.endswith(\".mzML\")]\n",
    "df[\"sample_name\"]=df[\"sample_name\"].replace(\".mzML\", value=\"\", regex=True)\n",
    "df[\"comment\"] = \" \"\n",
    "df[\"MAPnumber\"] = \" \"\n",
    "df.to_csv(os.path.join(\"config\", \"dataset.tsv\"), sep=\"\\t\")\n",
    "df.to_csv(os.path.join(\"config\", \"samples.tsv\"), sep=\"\\t\")\n",
    "df"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "651fe67a",
   "metadata": {},
   "source": [
    "##### `Define blanks/QCs/controls:` "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3fcdf5f0",
   "metadata": {},
   "outputs": [],
   "source": [
    "fList =input(\"Please enter a list of comma separated filenames for your blanks and/or QCs samples from the filelist: \").split(\",\")\n",
    "blank_DF = pd.DataFrame({\"sample_name\":fList})\n",
    "for i, blank in enumerate(zip(blank_DF.index, blank_DF[\"sample_name\"])):\n",
    "    for i, filename in zip(df.index, df[\"sample_name\"]):\n",
    "        if blank==filename:\n",
    "            blank_DF[\"sample_name\"][i] = df[\"sample_name\"][i]\n",
    "    blank_DF= blank_DF.dropna(how=\"all\")\n",
    "    blank_DF.to_csv(os.path.join(\"config\", \"blanks.tsv\"), sep=\"\\t\")\n",
    "\n",
    "blank_DF= pd.read_csv(os.path.join(\"config\", \"blanks.tsv\"), sep=\"\\t\", index_col=\"Unnamed: 0\")\n",
    "blank_DF[\"sample_name\"]= blank_DF[\"sample_name\"].astype(str)\n",
    "sample_DF= pd.DataFrame()\n",
    "if len(blank_DF)==0:\n",
    "    df.to_csv(os.path.join(\"config\", \"samples.tsv\"), sep=\"\\t\")\n",
    "else:\n",
    "    sample_DF= df[df[\"sample_name\"].str.contains(\"|\".join(blank_DF[\"sample_name\"]))==False]\n",
    "    sample_DF.to_csv(os.path.join(\"config\", \"samples.tsv\"), sep=\"\\t\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "078201c1",
   "metadata": {},
   "source": [
    "##### `Create a detailed GNPS metadata table:`\n",
    "This is datafile-dependent so it is preferable to do it interactively through a Jupyter notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bcb44573",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a metadata table from the list of mzML files compatible for GNPS\n",
    "\n",
    "metadata = pd.DataFrame()\n",
    "metadata[\"filename\"] = [file for file in os.listdir(os.path.join(\"data\", \"mzML\")) if file.endswith(\".mzML\")]\n",
    "metadata[\"ATTRIBUTE_MAPID\"]= [\"MAP\" + str(i) for i in range(len(metadata))]\n",
    "metadata['ATTRIBUTE_compound'] = metadata['filename'].replace(\".mzML\", value=\"\", regex=True)\n",
    "metadata['ATTRIBUTE_genomeID']=metadata['filename'].str.extract(r'(NBC_?\\d*|NBC?\\d*)')\n",
    "metadata['ATTRIBUTE_genomeID']= metadata['ATTRIBUTE_genomeID'].fillna(\"blank\")\n",
    "metadata['ATTRIBUTE_genomeIDMDNA']=metadata['filename'].str.extract(r'(MDNAWGS?\\d*|MDNA_WGS_?\\d*)')\n",
    "metadata['ATTRIBUTE_genomeID']=metadata['ATTRIBUTE_genomeID'].fillna(metadata['ATTRIBUTE_genomeIDMDNA'])\n",
    "metadata[\"ATTRIBUTE_media\"]= metadata['filename'].str.extract(r'(ISP2|DNPM|FPY12|MA|soyM\\d*)')\n",
    "metadata[\"ATTRIBUTE_comment\"]= metadata['ATTRIBUTE_genomeID'].astype(str) +\"_\" + metadata[\"ATTRIBUTE_media\"].astype(str)\n",
    "metadata=metadata.drop(columns=\"ATTRIBUTE_genomeIDMDNA\")\n",
    "metadata.to_csv(os.path.join(\"results\", \"GNPSexport\", \"metadata.tsv\"), sep='\\t', index= None)\n",
    "metadata"
   ]
  }
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