DatamodelExample0_3.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e4b6ddc4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Collecting sdRDM\n",
      "  Using cached sdRDM-0.0.3-py3-none-any.whl (47 kB)\n",
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      "Installing collected packages: sdRDM\n",
      "Successfully installed sdRDM-0.0.3\n",
      "Defaulting to user installation because normal site-packages is not writeable\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
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     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "Defaulting to user installation because normal site-packages is not writeable\n",
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      "Defaulting to user installation because normal site-packages is not writeable\n",
      "\u001b[31mERROR: Could not find a version that satisfies the requirement subprocess (from versions: none)\u001b[0m\u001b[31m\n",
      "\u001b[0m\u001b[31mERROR: No matching distribution found for subprocess\u001b[0m\u001b[31m\n",
      "\u001b[0mDefaulting to user installation because normal site-packages is not writeable\n",
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     ]
    }
   ],
   "source": [
    "# Install needed packages\n",
    "# biopython for biological analitical methods\n",
    "# elementpath for tree itiration\n",
    "# pandas for the construction of a dataframe from the xml file\n",
    "# SQLAlchemy and db-sqlite3 for database parsing from the dataframe\n",
    "!pip install biopython\n",
    "!pip install elementpath\n",
    "!pip install pandas\n",
    "!pip install SQLAlchemy\n",
    "!pip install db-sqlite3\n",
    "!pip install pandasql\n",
    "!pip3 install taxoniq\n",
    "!pip install nglview\n",
    "!pip install biopandas\n",
    "!pip install tabulate\n",
    "!pip install collection\n",
    "!pip install contextlib2\n",
    "!pip install fuzzywuzzy\n",
    "!pip install pyhmmer\n",
    "!pip install sto\n",
    "!pip install bio\n",
    "!pip install hmmlearn\n",
    "!pip install unipressed\n",
    "!pip install uniprot\n",
    "!pip install requests\n",
    "!pip install subprocess\n",
    "!pip install dict2xml \n",
    "!pip install minidom-ext\n",
    "!pip install flatten-json\n",
    "!pip install cdifflib\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "18b00f11",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Collecting git+https://github.com/JR-1991/software-driven-rdm.git\n",
      "  Cloning https://github.com/JR-1991/software-driven-rdm.git to /tmp/pip-req-build-gy9wlp2s\n",
      "  Running command git clone --filter=blob:none --quiet https://github.com/JR-1991/software-driven-rdm.git /tmp/pip-req-build-gy9wlp2s\n",
      "  Resolved https://github.com/JR-1991/software-driven-rdm.git to commit 6d29fddb754c2dfce5f3ddec709bcf84a18e29b3\n",
      "  Preparing metadata (setup.py) ... \u001b[?25ldone\n",
      "\u001b[?25hRequirement already satisfied: GitPython in /home/maxim/.local/lib/python3.8/site-packages (from sdRDM==0.0.4) (3.1.29)\n",
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      "Requirement already satisfied: gitdb<5,>=4.0.1 in /home/maxim/.local/lib/python3.8/site-packages (from GitPython->sdRDM==0.0.4) (4.0.10)\n",
      "Requirement already satisfied: MarkupSafe>=2.0 in /home/maxim/.local/lib/python3.8/site-packages (from jinja2->sdRDM==0.0.4) (2.1.1)\n",
      "Requirement already satisfied: greenlet!=0.4.17 in /home/maxim/.local/lib/python3.8/site-packages (from sqlalchemy->sdRDM==0.0.4) (2.0.1)\n",
      "Requirement already satisfied: decorator>=3.4.0 in /usr/lib/python3/dist-packages (from validators->sdRDM==0.0.4) (4.4.2)\n",
      "Requirement already satisfied: smmap<6,>=3.0.1 in /home/maxim/.local/lib/python3.8/site-packages (from gitdb<5,>=4.0.1->GitPython->sdRDM==0.0.4) (5.0.0)\n"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "!{sys.executable} -m pip install git+https://github.com/JR-1991/software-driven-rdm.git"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "7e3e9c1a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# query protein sequence input\n",
    "from Bio import SeqIO\n",
    "protein_seq = SeqIO.read(\"sequence.842.fasta\", \"fasta\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "26304330",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Seq('HPETLVKVKDAEDQLGARVGYIELDLNSGKILESFRPEERFPMMSTFKVLLCGA...KHW')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# double check the sequence\n",
    "protein_seq.seq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "534ffb5a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# run an online blast search in the NCBI database\n",
    "from Bio.Blast import NCBIWWW\n",
    "result_handle = NCBIWWW.qblast(\"blastp\", \"pdb\", protein_seq.seq) # pdb - protein data bank"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "bcceb543",
   "metadata": {},
   "outputs": [],
   "source": [
    "# save the ncbi search results as an xml document\n",
    "with open(\"TEM-1.xml\", \"w\") as save_to:\n",
    "    save_to.write(result_handle.read())\n",
    "    result_handle.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "40751340",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import sdRDM package\n",
    "import sdRDM\n",
    "from sdRDM import DataModel\n",
    "from sdRDM.database import build_sql_database"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "60a36669",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ProteinSequence\n",
      "├── id\n",
      "├── protein_sequence_id\n",
      "├── name\n",
      "├── amino_acid_sequence\n",
      "├── protein_database_name\n",
      "│   └── ProteinDatabase\n",
      "│       ├── id\n",
      "│       ├── database\n",
      "│       └── link_to_database\n",
      "└── protein_organism_id\n",
      "    └── Organism\n",
      "        ├── id\n",
      "        ├── organism_name\n",
      "        └── ncbi_taxonomy_id\n"
     ]
    }
   ],
   "source": [
    "#import the data base\n",
    "pyeed = DataModel.from_git(\"https://github.com/maxim945/PyEED-Fullprototype.git\")\n",
    "#visualize for each separate table\n",
    "pyeed.ProteinSequence.visualize_tree()\n",
    "#pyeed.DNASequence.visualize_tree()\n",
    "#pyeed.StandardNumberingScheme.visualize_tree()\n",
    "#pyeed.ProteinDatabase.visualize_tree()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a48bd091",
   "metadata": {},
   "source": [
    "This part of the code updated to itirate the data directly into the database, unlike in the previouse versions where you had to make a dataframe and then send it using SQL into the database here it goes directly from the source.\n",
    "NOTE!, to the full pipline like in the previouse versions you still should turn it into a dataframe for the "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "299610d7",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# convert the xml to a dataframe\n",
    "from sdRDM import DataModel\n",
    "import xml.etree.ElementTree as ET\n",
    "\n",
    "# PARSE XML\n",
    "tree = ET.parse('TEM-1.xml')\n",
    "root = tree.getroot()\n",
    "\n",
    "# Create a dataframe with 50 rows and 1 column\n",
    "# search for the specific hits in the xml file\n",
    "for child in root.iter():\n",
    "    if child.tag == 'BlastOutput_db':\n",
    "        BlastOutput_db=child.text.strip()\n",
    "    elif child.tag == 'Hit_accession':\n",
    "        Hit_accession=child.text.strip()\n",
    "    elif child.tag == 'Hit_def':\n",
    "        Hit_def=child.text.strip()\n",
    "    elif child.tag == 'Hsp_midline':\n",
    "        Hsp_midline=child.text.strip()\n",
    "\n",
    "        #export the data directly into the database\n",
    "        #chose the table (ProteinSequence) to which the data will be exported\n",
    "        #to each [Column Name] = [XML data] \n",
    "        #alocate into the database\n",
    "        dataset = pyeed.ProteinSequence(\n",
    "        protein_sequence_id=Hit_accession,\n",
    "        name=Hit_def,\n",
    "        amino_acid_sequence=Hsp_midline)\n",
    "        dataset.to_sql(loc=\"./TEM-1.db\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0bafc5b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "#build the database for each table\n",
    "build_sql_database(pyeed.ProteinSequence, loc=\"./TEM-1.db\")\n",
    "#build_sql_database(pyeed.ProteinDatabase, loc=\"./TEM-1.db\")\n",
    "#build_sql_database(pyeed.StandardNumberingScheme, loc=\"./TEM-1.db\")"
   ]
  }
 ],
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