{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "3ab47c20-100c-45cf-b564-37dafeb094d5",
   "metadata": {
    "tags": [],
    "user_expressions": []
   },
   "source": [
    "# Biopython Case Studies"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d50dc65e",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "## Prerequisites\n",
    "\n",
    "Install required packages:\n",
    "\n",
    "```bash\n",
    "pip install biopython pandas\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8bd43c24",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.13/site-packages/Bio/pairwise2.py:278: BiopythonDeprecationWarning: Bio.pairwise2 has been deprecated, and we intend to remove it in a future release of Biopython. As an alternative, please consider using Bio.Align.PairwiseAligner as a replacement, and contact the Biopython developers if you still need the Bio.pairwise2 module.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "from Bio import SeqIO, Entrez, pairwise2\n",
    "from Bio.Blast import NCBIWWW, NCBIXML\n",
    "from Bio.Seq import Seq\n",
    "from Bio.SeqRecord import SeqRecord\n",
    "from datetime import datetime\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "INPUT_FASTA = \"myseq.fa\"\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c809623-94aa-4de8-8b18-ab6bc0ed8eee",
   "metadata": {},
   "source": [
    "## Part I Identify Unknown Sequence via BLAST"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7cfc64e5",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "### Step 1: Import the Unknown Sequence into Python Running BLAST over the Internet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "020d25ea",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Submitting BLAST for sequence_unknown\n"
     ]
    }
   ],
   "source": [
    "record = list(SeqIO.parse(INPUT_FASTA, \"fasta\"))[0]\n",
    "print(f\"Submitting BLAST for {record.id}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "fff812a8-398f-45ef-b1e1-37b691b67a80",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ID: sequence_unknown\n",
      "Name: sequence_unknown\n",
      "Description: sequence_unknown\n",
      "Number of features: 0\n",
      "Seq('CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGT...GCC')\n"
     ]
    }
   ],
   "source": [
    "print(record)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9658c82-d348-42b8-b725-2aff35c88bd6",
   "metadata": {},
   "source": [
    "### Step 2: Running BLAST over the Internet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "8b55a09a-e73b-4bc2-aab4-86cab16c59a6",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BLAST completed\n"
     ]
    }
   ],
   "source": [
    "result_handle = NCBIWWW.qblast(\"blastn\", \"nt\", str(record.seq))\n",
    "# blast_record = NCBIXML.read(result_handle)\n",
    "print(\"BLAST completed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a1351fde-8a8d-4918-a5f0-36cadf93d261",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function qblast in module Bio.Blast.NCBIWWW:\n",
      "\n",
      "qblast(\n",
      "    program,\n",
      "    database,\n",
      "    sequence,\n",
      "    url_base='https://blast.ncbi.nlm.nih.gov/Blast.cgi',\n",
      "    auto_format=None,\n",
      "    composition_based_statistics=None,\n",
      "    db_genetic_code=None,\n",
      "    endpoints=None,\n",
      "    entrez_query='(none)',\n",
      "    expect=10.0,\n",
      "    filter=None,\n",
      "    gapcosts=None,\n",
      "    genetic_code=None,\n",
      "    hitlist_size=50,\n",
      "    i_thresh=None,\n",
      "    layout=None,\n",
      "    lcase_mask=None,\n",
      "    matrix_name=None,\n",
      "    nucl_penalty=None,\n",
      "    nucl_reward=None,\n",
      "    other_advanced=None,\n",
      "    perc_ident=None,\n",
      "    phi_pattern=None,\n",
      "    query_file=None,\n",
      "    query_believe_defline=None,\n",
      "    query_from=None,\n",
      "    query_to=None,\n",
      "    searchsp_eff=None,\n",
      "    service=None,\n",
      "    threshold=None,\n",
      "    ungapped_alignment=None,\n",
      "    word_size=None,\n",
      "    short_query=None,\n",
      "    alignments=500,\n",
      "    alignment_view=None,\n",
      "    descriptions=500,\n",
      "    entrez_links_new_window=None,\n",
      "    expect_low=None,\n",
      "    expect_high=None,\n",
      "    format_entrez_query=None,\n",
      "    format_object=None,\n",
      "    format_type='XML',\n",
      "    ncbi_gi=None,\n",
      "    results_file=None,\n",
      "    show_overview=None,\n",
      "    megablast=None,\n",
      "    template_type=None,\n",
      "    template_length=None,\n",
      "    username='blast',\n",
      "    password=None\n",
      ")\n",
      "    BLAST search using NCBI's QBLAST server.\n",
      "\n",
      "    Supports all parameters of the old qblast API for Put and Get.\n",
      "\n",
      "    Please note that NCBI uses the new Common URL API for BLAST searches\n",
      "    on the internet (https://blast.ncbi.nlm.nih.gov/doc/blast-help/urlapi.html).\n",
      "    Thus, some of the parameters used by this function are not (or are no longer)\n",
      "    officially supported by NCBI. Although they are still functioning, this\n",
      "    may change in the future.\n",
      "\n",
      "    Some useful parameters:\n",
      "\n",
      "     - program        blastn, blastp, blastx, tblastn, or tblastx (lower case)\n",
      "     - database       Which database to search against (e.g. \"nr\").\n",
      "     - sequence       The sequence to search.\n",
      "     - ncbi_gi        TRUE/FALSE whether to give 'gi' identifier.\n",
      "     - descriptions   Number of descriptions to show.  Def 500.\n",
      "     - alignments     Number of alignments to show.  Def 500.\n",
      "     - expect         An expect value cutoff.  Def 10.0.\n",
      "     - matrix_name    Specify an alt. matrix (PAM30, PAM70, BLOSUM80, BLOSUM45).\n",
      "     - filter         \"none\" turns off filtering.  Default no filtering\n",
      "     - format_type    \"HTML\", \"Text\", \"ASN.1\", or \"XML\".  Def. \"XML\".\n",
      "     - entrez_query   Entrez query to limit Blast search - only applies when searching nucleotide BLASTDBs\n",
      "     - hitlist_size   Number of hits to return. Default 50\n",
      "     - megablast      TRUE/FALSE whether to use MEga BLAST algorithm (blastn only)\n",
      "     - short_query    TRUE/FALSE whether to adjust the search parameters for a\n",
      "                      short query sequence. Note that this will override\n",
      "                      manually set parameters like word size and e value. Turns\n",
      "                      off when sequence length is > 30 residues. Default: None.\n",
      "     - service        plain, psi, phi, rpsblast, megablast (lower case)\n",
      "\n",
      "    This function does no checking of the validity of the parameters\n",
      "    and passes the values to the server as is.  More help is available at:\n",
      "    https://blast.ncbi.nlm.nih.gov/doc/blast-help/urlapi.html\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(NCBIWWW.qblast)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dc45708a-d135-4752-ba66-1deec9943d98",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "### Step 3: Import The BLAST Record (XML format)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "4c7bfd13-73e2-4e7e-869a-0a89685eb3b3",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "blast_record = NCBIXML.read(result_handle)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "0a561860-f58a-4ce2-8568-00529f725b69",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Bio.Blast.NCBIXML.Blast at 0x139398cd0>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "blast_record"
   ]
  },
  {
   "attachments": {
    "10ce45ae-646e-429f-8ef6-34ce31d34bbb.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "id": "16849276-a65c-48d2-93a4-0112beed7f35",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "![BlastR.png](attachment:10ce45ae-646e-429f-8ef6-34ce31d34bbb.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d519a8f-d1ca-40ba-9df3-99448e2eb31e",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "### Step 4: Parsing BLAST Output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "90cb8d68-054e-4a01-8b09-36ea39d2237f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(blast_record.alignments)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac451939-86a5-4f28-9256-1e424fea1165",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "Best Match For DNA Sequence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "2418ffb1-ab26-4eeb-85b8-a82df7157c43",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "****Alignment****\n",
      "sequence: gi|2695886215|gb|OR084930.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT003007, partial genome\n",
      "length: 18922\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885795|gb|OR084888.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT002129, partial genome\n",
      "length: 18942\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885865|gb|OR084895.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT002138, partial genome\n",
      "length: 18532\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885945|gb|OR084903.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT002151, partial genome\n",
      "length: 18532\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885725|gb|OR084881.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT002121, partial genome\n",
      "length: 18532\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695886125|gb|OR084921.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT003018, partial genome\n",
      "length: 18941\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885745|gb|OR084883.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT002123, partial genome\n",
      "length: 18832\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885885|gb|OR084897.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT002140, partial genome\n",
      "length: 18832\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885655|gb|OR084874.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT002107, partial genome\n",
      "length: 18832\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885605|gb|OR084869.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT000796, partial genome\n",
      "length: 18921\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695886145|gb|OR084923.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Monieka-RDCEQT003256, partial genome\n",
      "length: 18832\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885555|gb|OR084864.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT000492, partial genome\n",
      "length: 18532\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695886115|gb|OR084920.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT003014, partial genome\n",
      "length: 18930\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885665|gb|OR084875.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT002111, partial genome\n",
      "length: 18832\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885845|gb|OR084893.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT002136, partial genome\n",
      "length: 18532\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885595|gb|OR084868.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT000617, partial genome\n",
      "length: 18532\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695886015|gb|OR084910.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Bomongo-RDCEQT002163, partial genome\n",
      "length: 18932\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885575|gb|OR084866.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT000571, partial genome\n",
      "length: 18936\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885825|gb|OR084891.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT002134, partial genome\n",
      "length: 18532\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885385|gb|OR084847.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Tumba-RDCEQT000199, partial genome\n",
      "length: 18574\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885525|gb|OR084861.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT000456, partial genome\n",
      "length: 18832\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695886025|gb|OR084911.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT002164, partial genome\n",
      "length: 18832\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885905|gb|OR084899.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT002144, partial genome\n",
      "length: 18832\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885695|gb|OR084878.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT002117, partial genome\n",
      "length: 18832\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|3018473336|emb|OZ276552.1| Zaire ebolavirus isolate Ebola virus/VECTOR/C.porcellus-lab/COD/1976/Mayinga_NML genome assembly, complete genome: monopartite\n",
      "length: 18582\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695886045|gb|OR084913.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/mbandaka-RDCEQT002502, partial genome\n",
      "length: 18832\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885635|gb|OR084872.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT002103, partial genome\n",
      "length: 18832\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695886205|gb|OR084929.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT002148, partial genome\n",
      "length: 18939\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695886095|gb|OR084918.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT003011, partial genome\n",
      "length: 18531\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885515|gb|OR084860.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT000301, partial genome\n",
      "length: 18532\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885855|gb|OR084894.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT002137, partial genome\n",
      "length: 18531\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885415|gb|OR084850.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT000010, partial genome\n",
      "length: 18943\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695886195|gb|OR084928.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT000300, partial genome\n",
      "length: 18927\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2501520155|gb|OQ784121.1| Mutant Zaire ebolavirus rMA-EBOV-ZsGnLuc, complete genome\n",
      "length: 20233\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885435|gb|OR084852.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT000017, partial genome\n",
      "length: 18940\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885545|gb|OR084863.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT000474, partial genome\n",
      "length: 18531\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885465|gb|OR084855.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT000042, partial genome\n",
      "length: 18832\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885395|gb|OR084848.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Tumba-RDCEQT000029, partial genome\n",
      "length: 18287\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885585|gb|OR084867.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT000616, partial genome\n",
      "length: 18532\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885645|gb|OR084873.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT002106, partial genome\n",
      "length: 18832\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885925|gb|OR084901.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT002146, partial genome\n",
      "length: 18832\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695886085|gb|OR084917.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT003008, partial genome\n",
      "length: 18532\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885445|gb|OR084853.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT000018, partial genome >gi|2695885485|gb|OR084857.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT000074, partial genome\n",
      "length: 18939\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885615|gb|OR084870.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT000869, partial genome\n",
      "length: 18532\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885815|gb|OR084890.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT002132, partial genome\n",
      "length: 18532\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885475|gb|OR084856.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT000046, partial genome\n",
      "length: 18831\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885935|gb|OR084902.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT002149, partial genome\n",
      "length: 18832\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695886035|gb|OR084912.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT002501, partial genome\n",
      "length: 18832\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2501520146|gb|OQ784120.1| Mutant Zaire ebolavirus rMA-EBOV-nLuc-ZsG, complete genome\n",
      "length: 20302\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "****Alignment****\n",
      "sequence: gi|2695885875|gb|OR084896.1| Zaire ebolavirus isolate Ebolavirus/H.sapiens-wt/COD/2020/Mbandaka-RDCEQT002139, partial genome\n",
      "length: 18832\n",
      "e value: 3.21162e-28\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "CATGCTACGGTGCTAAAAGCATTACGCCCTATAGTGATTTTCGAGACATACTGTGTTTTTAAATATAGTATTGCC\n"
     ]
    }
   ],
   "source": [
    "E_VALUE_THRESH = 0.01\n",
    "\n",
    "for alignment in blast_record.alignments:\n",
    "    for hsp in alignment.hsps:\n",
    "        if hsp.expect < E_VALUE_THRESH:\n",
    "            print(\"****Alignment****\")\n",
    "            print(\"sequence:\", alignment.title)\n",
    "            print(\"length:\", alignment.length)\n",
    "            print(\"e value:\", hsp.expect)\n",
    "            print(hsp.query)\n",
    "            print(hsp.match)\n",
    "            print(hsp.sbjct)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f7c18ab-2c6d-4ddc-aef9-621f2c6d9e8e",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "## Part II: Some other Useful Biopython Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "bdc23597-efcd-4fc3-8423-ac3cc633491a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Seq('ACGAGGACAGAT')"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from Bio.Seq import Seq\n",
    "my_seq= Seq(\"ACGAGGACAGAT\") ## create a DNA sequence record in BioPython\n",
    "my_seq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "57c913cb-c7bf-42df-93bf-2d112358616e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ACGAGGACAGAT\n"
     ]
    }
   ],
   "source": [
    "print(my_seq)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d82e57f-9703-406d-a51a-9dfb0999d138",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "### Nucleotide Methods: complement, reverse_complement, trnaslate, ...etc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c785cb99-7290-46c3-b449-ed4092f85334",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Seq('TGCTCCTGTCTA')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_seq.complement()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "77f992af-1558-4951-88f4-035990d3884e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Seq('ATCTGTCCTCGT')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_seq.reverse_complement()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5d532e4a-76e1-4715-8781-012c36d6fda4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Seq('TRTD')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_seq.translate()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a734fe66-60f7-4382-ae86-4f76663b3571",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "### General Methods: find, count ...etc"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a24a477-ea59-476a-99d4-539e5b7b2b51",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "#### Count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f0c41cf3-f3c4-491a-bcfd-bef317a96dab",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5\n",
      "4\n"
     ]
    }
   ],
   "source": [
    "print(my_seq.count(\"A\"))  # count of A\n",
    "print(my_seq.count(\"G\"))  # count of G"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "7ea99eb1-0906-4df6-9553-8faff420e5f1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n"
     ]
    }
   ],
   "source": [
    "print(my_seq.count(\"ACG\"))  ##Counts non-overlapping occurrences"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4af38286-1eb5-4b8b-93d2-3adff77b4140",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "#### Find"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ce7cf9db-f073-4d67-bd82-f675de830816",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ACGAGGACAGAT\n",
      "0\n"
     ]
    }
   ],
   "source": [
    "print(my_seq)\n",
    "position = my_seq.find(\"A\")\n",
    "print(position)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8eda3421-4764-490d-b29a-1ea3c5c33668",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "## Part III: Motif Finding with Biopython"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a557c935-851c-4086-94cc-81c2e5b521b7",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from Bio import motifs\n",
    "from Bio.Seq import Seq\n",
    "\n",
    "sequences = [\n",
    "    Seq(\"ATGCA\"),\n",
    "    Seq(\"ATGGA\"),\n",
    "    Seq(\"ATGTA\"),\n",
    "    Seq(\"ATGCA\"),\n",
    "    Seq(\"ATGCC\")\n",
    "]\n",
    "\n",
    "motif = motifs.create(sequences)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "2758dffe-94c5-40bf-bd73-07f9cf405cb4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Bio.motifs.Motif at 0x1363667b0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "motif"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "334039e9-5764-4bfb-8376-a70877edbe56",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        0      1      2      3      4\n",
      "A:   5.00   0.00   0.00   0.00   4.00\n",
      "C:   0.00   0.00   0.00   3.00   1.00\n",
      "G:   0.00   0.00   5.00   1.00   0.00\n",
      "T:   0.00   5.00   0.00   1.00   0.00\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(motif.counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "5f3cd07f-303c-474e-ad12-29a281fa60a5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        0      1      2      3      4\n",
      "A:   0.79   0.07   0.07   0.07   0.64\n",
      "C:   0.07   0.07   0.07   0.50   0.21\n",
      "G:   0.07   0.07   0.79   0.21   0.07\n",
      "T:   0.07   0.79   0.07   0.21   0.07\n",
      "\n"
     ]
    }
   ],
   "source": [
    "ppm=motif.counts.normalize(pseudocounts=0.5)\n",
    "print(ppm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "e048e635-a449-43a9-bbc0-af28e141e32d",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "motif.weblogo(\"motif.png\")"
   ]
  },
  {
   "attachments": {
    "45231fa7-15ea-43ee-bb64-4007fab809d6.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "id": "359f78cc-9bd6-4b01-8fb2-669211ac9924",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "![motif.png](attachment:45231fa7-15ea-43ee-bb64-4007fab809d6.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "13be5243-e9a0-4adf-be17-dbbeed6c92ec",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        0      1      2      3      4\n",
      "A:   1.65  -1.81  -1.81  -1.81   1.36\n",
      "C:  -1.81  -1.81  -1.81   1.00  -0.22\n",
      "G:  -1.81  -1.81   1.65  -0.22  -1.81\n",
      "T:  -1.81   1.65  -1.81  -0.22  -1.81\n",
      "\n"
     ]
    }
   ],
   "source": [
    "motif.pseudocounts = 0.5\n",
    "motif.background = {\"A\": 0.25, \"C\": 0.25, \"G\": 0.25, \"T\": 0.25}\n",
    "\n",
    "# Compute PSSM\n",
    "pssm = motif.pssm\n",
    "print(pssm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a402adf1-0f1f-44ab-a611-f35df158c320",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rows = len(pssm.alphabet)\n",
    "cols = pssm.length\n",
    "cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "debfdb3d-afd0-49ab-ad90-784d4e5b839d",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# ---------- Helper: score a k-mer of length L ----------\n",
    "def score_kmer(kmer, pssm_matrix):\n",
    "    L= pssm_matrix.length\n",
    "    kmer = str(kmer).upper()\n",
    "    if len(kmer) != L:\n",
    "        raise ValueError(f\"k-mer length must be {L}\")\n",
    "    total = 0.0\n",
    "    for i, base in enumerate(kmer):\n",
    "        if base not in pssm_matrix:\n",
    "            raise ValueError(f\"Unknown base {base}\")\n",
    "        total += pssm_matrix[base][i]\n",
    "    return total\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "0f13195f-b3cf-4b99-91f4-accff7d11aac",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "All scored windows (position, strand, seq, score):\n",
      "(0, '+', 'GGGAT', -5.577342991650724)\n",
      "(0, '-', 'ATCCC', 2.2744060497653344)\n",
      "(1, '+', 'GGATG', -7.451812109566864)\n",
      "(1, '-', 'CATCC', -4.644457187509261)\n",
      "(2, '+', 'GATGC', -5.866849608845708)\n",
      "(2, '-', 'GCATC', -5.866849608845708)\n",
      "(3, '+', 'ATGCA', 7.318800169123788)\n",
      "(3, '-', 'TGCAT', -9.03677461028802)\n",
      "(4, '+', 'TGCAA', -5.866849608845708)\n",
      "(4, '-', 'TTGCA', 3.859368550486491)\n",
      "(5, '+', 'GCAAA', -5.866849608845708)\n",
      "(5, '-', 'TTTGC', -2.407417990208411)\n",
      "(6, '+', 'CAAAA', -5.866849608845708)\n",
      "(6, '-', 'TTTTG', -3.992380490929567)\n",
      "(7, '+', 'AAAAT', -5.577342991650724)\n",
      "(7, '-', 'ATTTT', -0.5329488722922697)\n",
      "(8, '+', 'AAATG', -3.992380490929567)\n",
      "(8, '-', 'CATTT', -7.451812109566864)\n",
      "(9, '+', 'AATGG', -3.992380490929567)\n",
      "(9, '-', 'CCATT', -7.451812109566864)\n",
      "(10, '+', 'ATGGA', 6.096407747787341)\n",
      "(10, '-', 'TCCAT', -9.03677461028802)\n",
      "(11, '+', 'TGGAA', -2.407417990208411)\n",
      "(11, '-', 'TTCCA', 0.39993693184919343)\n",
      "(12, '+', 'GGAAT', -9.03677461028802)\n",
      "(12, '-', 'ATTCC', 2.2744060497653344)\n",
      "(13, '+', 'GAATG', -7.451812109566864)\n",
      "(13, '-', 'CATTC', -5.866849608845708)\n",
      "(14, '+', 'AATGT', -3.992380490929567)\n",
      "(14, '-', 'ACATT', -3.992380490929567)\n",
      "(15, '+', 'ATGTA', 6.096407747787341)\n",
      "(15, '-', 'TACAT', -9.03677461028802)\n"
     ]
    }
   ],
   "source": [
    "def scan_sequence(seq, pssm_matrix, threshold=None, include_revcomp=True):\n",
    "    seq = str(seq).upper()\n",
    "    hits = []\n",
    "    L= pssm_matrix.length\n",
    "    for i in range(len(seq) - L + 1):\n",
    "        window = seq[i:i+L]\n",
    "        sc = score_kmer(window, pssm_matrix)\n",
    "        strand = \"+\"\n",
    "        if threshold is None or sc >= threshold:\n",
    "            hits.append((i, strand, window, sc))\n",
    "        if include_revcomp:\n",
    "            # score reverse complement of the window (so we find motif on both strands)\n",
    "            rc = str(Seq(window).reverse_complement())\n",
    "            sc_rc = score_kmer(rc, pssm_matrix)\n",
    "            if threshold is None or sc_rc >= threshold:\n",
    "                hits.append((i, \"-\", rc, sc_rc))\n",
    "    return hits\n",
    "\n",
    "long_seq = \"GGGATGCAAAATGGAATGTA\"\n",
    "hits = scan_sequence(long_seq, pssm, threshold=None)\n",
    "print(\"\\nAll scored windows (position, strand, seq, score):\")\n",
    "for h in hits:\n",
    "    print(h)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "203ccf84-7c51-4c67-859d-5f90996b812c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Max possible score: 7.3188\n",
      "Min possible score: -9.036775\n"
     ]
    }
   ],
   "source": [
    "# ---------- Useful diagnostics: max/min possible score ----------\n",
    "alphabet=[\"A\", \"C\", \"G\", \"T\"]\n",
    "L= pssm.length\n",
    "max_score = sum(max(pssm[b][i] for b in alphabet) for i in range(L))\n",
    "min_score = sum(min(pssm[b][i] for b in alphabet) for i in range(L))\n",
    "print(\"\\nMax possible score:\", round(max_score,6))\n",
    "print(\"Min possible score:\", round(min_score,6))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python (base)",
   "language": "python",
   "name": "base"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}