notebooks/app_workflows/W3_multiplexed_CRISPR-BEST.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## W3-CRISPR-mcBEST workflow\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "The workflow allows for the simultaneous targeted engineering of up to 28 individual situated bases in the genome of Streptomyces, as shown by Whitford et. al 2023, thereby enabling efficient single-step multi-target engineering13. Similar to workflow 2, this workflow employs the CRISPR-BEST methodology but instead of performing base-editing on a single gene the method incorporates multiple guide RNAs as an array into the same vector (Figure 4A). This significantly enhances the efficiency of high-throughput genetic studies. The pCRISPR-cBEST plasmid file can be downloaded on the page along with the genome file for S.coelicor (A3) and streptoAIM will generate your plasmids, primers, checking primers and analyze the overhangs the target genes(Figure 4, S6). \n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {},
      "outputs": [],
      "source": [
        "import sys\n",
        "import os\n",
        "from pydna.dseqrecord import Dseqrecord\n",
        "from teemi.build.PCR import primer_tm_neb\n",
        "import pandas as pd\n",
        "from datetime import datetime\n",
        "\n",
        "\n",
        "# Ensure the src directory is in the Python path\n",
        "project_root = os.path.abspath(os.path.join(os.getcwd(), '../../'))\n",
        "if project_root not in sys.path:\n",
        "    sys.path.insert(0, project_root)\n",
        "\n",
        "from streptocad.sequence_loading.sequence_loading import (\n",
        "    load_and_process_plasmid, \n",
        "    check_and_convert_input,\n",
        "    annotate_dseqrecord,\n",
        "    process_specified_gene_sequences_from_record)\n",
        "\n",
        "\n",
        "from streptocad.utils import polymerase_dict, dataframe_to_seqrecords, ProjectDirectory, extract_metadata_to_dataframe\n",
        "from streptocad.crispr.guideRNAcas3_9_12 import extract_sgRNAs, SgRNAargs\n",
        "from streptocad.crispr.crispr_best import (\n",
        "    identify_base_editing_sites,\n",
        "    filter_sgrnas_for_base_editing,\n",
        "    process_base_editing\n",
        ")\n",
        "\n",
        "from streptocad.cloning.golden_gate_cloning import (\n",
        "    GoldenGateCloning,\n",
        "    create_overhang_dataframe,\n",
        "    digest_amplicons_w_BsaI\n",
        ")\n",
        "\n",
        "from streptocad.primers.primer_analysis import analyze_primers_and_hairpins\n",
        "from streptocad.primers.primer_generation import create_idt_order_dataframe\n",
        "from streptocad.cloning.plasmid_processing import annotate_plasmid_with_sgrnas\n",
        "from streptocad.primers.primer_generation import find_best_check_primers_from_genome"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Inputs\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {},
      "outputs": [],
      "source": [
        "# 1 Add genome of choice (genbank, fasta)\n",
        "path_to_genome = '../../data/genomes/Streptomyces_coelicolor_A3_chromosome.gb'\n",
        "genome = load_and_process_plasmid(path_to_genome)\n",
        "\n",
        "# 2 Add plasmid \n",
        "path_to_plasmid = '../../data/plasmids/pCRISPR-MCBE_Csy4_kasopGFP.gb'\n",
        "clean_plasmid = load_and_process_plasmid(path_to_plasmid)\n",
        "\n",
        "# 3 Choose genes to knock out (list)\n",
        "genes_to_KO = ['SCO5087', 'SCO5089', 'SCO5090']\n",
        "#genes_to_KO = ['80000-100000', '4000-7000', '9000-14000','15000-20000']\n",
        "\n",
        "\n",
        "#### Advanced settings ####\n",
        "# 4 Filtering metrics for sgRNAs\n",
        "gc_upper = 0.72\n",
        "gc_lower = 0.2\n",
        "off_target_seed = 13\n",
        "off_target_upper = 10\n",
        "cas_type='cas9'\n",
        "number_of_sgRNAs_per_group = 2\n",
        "\n",
        "# 5 Choose polymerase and target melting temperature\n",
        "chosen_polymerase = polymerase_dict['Phusion High-Fidelity DNA Polymerase (GC Buffer)']\n",
        "melting_temperature = 60\n",
        "primer_concentration = 0.4 \n",
        "flanking_region=500\n",
        "\n",
        "\n",
        "# 6 Choose overlapping sequences for our plasmid we can use the following\n",
        "restriction_overhang_f = \"GATCGggtctcc\"\n",
        "restriction_overhang_r = \"GATCAGGTCTCg\"\n",
        "backbone_overhang_f = \"cATG\"\n",
        "backbone_overhang_r = \"cTAG\"\n",
        "cys4 = \"gTTCACTGCCGTATAGGCAGCTAAGAAA\"\n",
        "sgRNA_handle_cys4_site = [Dseqrecord('GTTTTAGAGCTAGAAATAGCAAGTTAAAATAAGGCTAGTCCGTTATCAACTTGAAAAAGTGGCACCGAGTCGGTGCTTTTTT', name = 'sgRNA_handle_cys4')]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "pCRISPR-mcBEST\n"
          ]
        }
      ],
      "source": [
        "print(clean_plasmid.id)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Computation"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "False\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "25824"
            ]
          },
          "execution_count": 4,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "target_dict, genes_to_KO, annotation_input = check_and_convert_input(genes_to_KO)\n",
        "\n",
        "print(annotation_input)\n",
        "if annotation_input == True:\n",
        "    genome = annotate_dseqrecord(genome, target_dict)\n",
        "\n",
        "\n",
        "len(genome.features)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Pam was found outside designated locus_tag: SCO5087. To incorporate this extent borders. Skipping to next locus tag.\n",
            "sgRNA generated were outside the designated border in SCO5087. To incorporate this extent borders. Skipping to next locus tag.\n",
            "Pam was found outside designated locus_tag: SCO5087. To incorporate this extent borders. Skipping to next locus tag.\n",
            "sgRNA generated were outside the designated border in SCO5087. To incorporate this extent borders. Skipping to next locus tag.\n",
            "sgRNA generated were outside the designated border in SCO5087. To incorporate this extent borders. Skipping to next locus tag.\n",
            "sgRNA generated were outside the designated border in SCO5089. To incorporate this extent borders. Skipping to next locus tag.\n",
            "sgRNA generated were outside the designated border in SCO5089. To incorporate this extent borders. Skipping to next locus tag.\n",
            "Pam was found outside designated locus_tag: SCO5090. To incorporate this extent borders. Skipping to next locus tag.\n",
            "sgRNA generated were outside the designated border in SCO5090. To incorporate this extent borders. Skipping to next locus tag.\n",
            "sgRNA generated were outside the designated border in SCO5090. To incorporate this extent borders. Skipping to next locus tag.\n",
            "sgRNA generated were outside the designated border in SCO5090. To incorporate this extent borders. Skipping to next locus tag.\n",
            "sgRNA generated were outside the designated border in SCO5090. To incorporate this extent borders. Skipping to next locus tag.\n",
            "sgRNA generated were outside the designated border in SCO5090. To incorporate this extent borders. Skipping to next locus tag.\n"
          ]
        },
        {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>strain_name</th>\n",
              "      <th>locus_tag</th>\n",
              "      <th>gene_loc</th>\n",
              "      <th>gene_strand</th>\n",
              "      <th>sgrna_strand</th>\n",
              "      <th>sgrna_loc</th>\n",
              "      <th>gc</th>\n",
              "      <th>pam</th>\n",
              "      <th>sgrna</th>\n",
              "      <th>sgrna_seed_sequence</th>\n",
              "      <th>off_target_count</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>334</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5090</td>\n",
              "      <td>5532706</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>32</td>\n",
              "      <td>0.65</td>\n",
              "      <td>CGG</td>\n",
              "      <td>TGGACCACCCGGTGTTCTCC</td>\n",
              "      <td>CCCGGTGTTCTCC</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>330</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5089</td>\n",
              "      <td>5532449</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>61</td>\n",
              "      <td>0.70</td>\n",
              "      <td>CGG</td>\n",
              "      <td>CGTGGAGTGCGCCGGTGAGA</td>\n",
              "      <td>TGCGCCGGTGAGA</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>329</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5089</td>\n",
              "      <td>5532449</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>65</td>\n",
              "      <td>0.70</td>\n",
              "      <td>CGG</td>\n",
              "      <td>GAGTGCGCCGGTGAGACGGA</td>\n",
              "      <td>CCGGTGAGACGGA</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>328</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5089</td>\n",
              "      <td>5532449</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>66</td>\n",
              "      <td>0.70</td>\n",
              "      <td>GGG</td>\n",
              "      <td>AGTGCGCCGGTGAGACGGAC</td>\n",
              "      <td>CGGTGAGACGGAC</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>326</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5089</td>\n",
              "      <td>5532449</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>80</td>\n",
              "      <td>0.70</td>\n",
              "      <td>CGG</td>\n",
              "      <td>ACGGACGGGACGGACCTGTC</td>\n",
              "      <td>GGACGGACCTGTC</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>108</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5087</td>\n",
              "      <td>5529801</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>1038</td>\n",
              "      <td>0.70</td>\n",
              "      <td>GGG</td>\n",
              "      <td>GATGTCCGTCGCGTCCGTGC</td>\n",
              "      <td>GTCGCGTCCGTGC</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>295</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5089</td>\n",
              "      <td>5532449</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>60</td>\n",
              "      <td>0.70</td>\n",
              "      <td>GGG</td>\n",
              "      <td>CTCACCGGCGCACTCCACGA</td>\n",
              "      <td>GCGCACTCCACGA</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>449</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5090</td>\n",
              "      <td>5532706</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>890</td>\n",
              "      <td>0.65</td>\n",
              "      <td>CGG</td>\n",
              "      <td>ACCCATCTGCGCGAGGTGCT</td>\n",
              "      <td>TGCGCGAGGTGCT</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>191</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5087</td>\n",
              "      <td>5529801</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>838</td>\n",
              "      <td>0.70</td>\n",
              "      <td>TGG</td>\n",
              "      <td>TACGCGGGACGGCTTCGTGC</td>\n",
              "      <td>GACGGCTTCGTGC</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5087</td>\n",
              "      <td>5529801</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>706</td>\n",
              "      <td>0.65</td>\n",
              "      <td>CGG</td>\n",
              "      <td>CAGCGCCGACGTGATGTTCG</td>\n",
              "      <td>GACGTGATGTTCG</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>279 rows × 11 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     strain_name locus_tag  gene_loc  gene_strand  sgrna_strand  sgrna_loc  \\\n",
              "334  NC_003888.3   SCO5090   5532706            1            -1         32   \n",
              "330  NC_003888.3   SCO5089   5532449            1             1         61   \n",
              "329  NC_003888.3   SCO5089   5532449            1             1         65   \n",
              "328  NC_003888.3   SCO5089   5532449            1             1         66   \n",
              "326  NC_003888.3   SCO5089   5532449            1             1         80   \n",
              "..           ...       ...       ...          ...           ...        ...   \n",
              "108  NC_003888.3   SCO5087   5529801            1            -1       1038   \n",
              "295  NC_003888.3   SCO5089   5532449            1            -1         60   \n",
              "449  NC_003888.3   SCO5090   5532706            1             1        890   \n",
              "191  NC_003888.3   SCO5087   5529801            1             1        838   \n",
              "200  NC_003888.3   SCO5087   5529801            1             1        706   \n",
              "\n",
              "       gc  pam                 sgrna sgrna_seed_sequence  off_target_count  \n",
              "334  0.65  CGG  TGGACCACCCGGTGTTCTCC       CCCGGTGTTCTCC                 0  \n",
              "330  0.70  CGG  CGTGGAGTGCGCCGGTGAGA       TGCGCCGGTGAGA                 0  \n",
              "329  0.70  CGG  GAGTGCGCCGGTGAGACGGA       CCGGTGAGACGGA                 0  \n",
              "328  0.70  GGG  AGTGCGCCGGTGAGACGGAC       CGGTGAGACGGAC                 0  \n",
              "326  0.70  CGG  ACGGACGGGACGGACCTGTC       GGACGGACCTGTC                 0  \n",
              "..    ...  ...                   ...                 ...               ...  \n",
              "108  0.70  GGG  GATGTCCGTCGCGTCCGTGC       GTCGCGTCCGTGC                 2  \n",
              "295  0.70  GGG  CTCACCGGCGCACTCCACGA       GCGCACTCCACGA                 2  \n",
              "449  0.65  CGG  ACCCATCTGCGCGAGGTGCT       TGCGCGAGGTGCT                 3  \n",
              "191  0.70  TGG  TACGCGGGACGGCTTCGTGC       GACGGCTTCGTGC                 3  \n",
              "200  0.65  CGG  CAGCGCCGACGTGATGTTCG       GACGTGATGTTCG                 3  \n",
              "\n",
              "[279 rows x 11 columns]"
            ]
          },
          "execution_count": 5,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Initialize SgRNAargs with desired parameters\n",
        "args = SgRNAargs(genome, \n",
        "                genes_to_KO,\n",
        "                step=['find', 'filter'],\n",
        "                gc_upper = gc_upper,\n",
        "                gc_lower = gc_lower,\n",
        "                off_target_seed = off_target_seed,\n",
        "                off_target_upper = off_target_upper,\n",
        "                cas_type='cas9'\n",
        "                )\n",
        "\n",
        "sgrna_df = extract_sgRNAs(args)\n",
        "sgrna_df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {},
      "outputs": [
        {
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>strain_name</th>\n",
              "      <th>locus_tag</th>\n",
              "      <th>gene_loc</th>\n",
              "      <th>gene_strand</th>\n",
              "      <th>sgrna_strand</th>\n",
              "      <th>sgrna_loc</th>\n",
              "      <th>gc</th>\n",
              "      <th>pam</th>\n",
              "      <th>sgrna</th>\n",
              "      <th>sgrna_seed_sequence</th>\n",
              "      <th>off_target_count</th>\n",
              "      <th>editing_context</th>\n",
              "      <th>editable_cytosines</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>334</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5090</td>\n",
              "      <td>5532706</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>32</td>\n",
              "      <td>0.65</td>\n",
              "      <td>CGG</td>\n",
              "      <td>TGGACCACCCGGTGTTCTCC</td>\n",
              "      <td>CCCGGTGTTCTCC</td>\n",
              "      <td>0</td>\n",
              "      <td>0,0,0,0,0</td>\n",
              "      <td>5,6,8,9,10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>330</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5089</td>\n",
              "      <td>5532449</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>61</td>\n",
              "      <td>0.70</td>\n",
              "      <td>CGG</td>\n",
              "      <td>CGTGGAGTGCGCCGGTGAGA</td>\n",
              "      <td>TGCGCCGGTGAGA</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>329</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5089</td>\n",
              "      <td>5532449</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>65</td>\n",
              "      <td>0.70</td>\n",
              "      <td>CGG</td>\n",
              "      <td>GAGTGCGCCGGTGAGACGGA</td>\n",
              "      <td>CCGGTGAGACGGA</td>\n",
              "      <td>0</td>\n",
              "      <td>1,1,0</td>\n",
              "      <td>6,8,9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>328</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5089</td>\n",
              "      <td>5532449</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>66</td>\n",
              "      <td>0.70</td>\n",
              "      <td>GGG</td>\n",
              "      <td>AGTGCGCCGGTGAGACGGAC</td>\n",
              "      <td>CGGTGAGACGGAC</td>\n",
              "      <td>0</td>\n",
              "      <td>1,1,0</td>\n",
              "      <td>5,7,8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>326</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5089</td>\n",
              "      <td>5532449</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>80</td>\n",
              "      <td>0.70</td>\n",
              "      <td>CGG</td>\n",
              "      <td>ACGGACGGGACGGACCTGTC</td>\n",
              "      <td>GGACGGACCTGTC</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>108</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5087</td>\n",
              "      <td>5529801</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>1038</td>\n",
              "      <td>0.70</td>\n",
              "      <td>GGG</td>\n",
              "      <td>GATGTCCGTCGCGTCCGTGC</td>\n",
              "      <td>GTCGCGTCCGTGC</td>\n",
              "      <td>2</td>\n",
              "      <td>0,0,0</td>\n",
              "      <td>6,7,10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>295</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5089</td>\n",
              "      <td>5532449</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>60</td>\n",
              "      <td>0.70</td>\n",
              "      <td>GGG</td>\n",
              "      <td>CTCACCGGCGCACTCCACGA</td>\n",
              "      <td>GCGCACTCCACGA</td>\n",
              "      <td>2</td>\n",
              "      <td>0,0,0,1</td>\n",
              "      <td>3,5,6,9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>449</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5090</td>\n",
              "      <td>5532706</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>890</td>\n",
              "      <td>0.65</td>\n",
              "      <td>CGG</td>\n",
              "      <td>ACCCATCTGCGCGAGGTGCT</td>\n",
              "      <td>TGCGCGAGGTGCT</td>\n",
              "      <td>3</td>\n",
              "      <td>0,0,0,1</td>\n",
              "      <td>3,4,7,10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>191</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5087</td>\n",
              "      <td>5529801</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>838</td>\n",
              "      <td>0.70</td>\n",
              "      <td>TGG</td>\n",
              "      <td>TACGCGGGACGGCTTCGTGC</td>\n",
              "      <td>GACGGCTTCGTGC</td>\n",
              "      <td>3</td>\n",
              "      <td>0,1,0</td>\n",
              "      <td>3,5,10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5087</td>\n",
              "      <td>5529801</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>706</td>\n",
              "      <td>0.65</td>\n",
              "      <td>CGG</td>\n",
              "      <td>CAGCGCCGACGTGATGTTCG</td>\n",
              "      <td>GACGTGATGTTCG</td>\n",
              "      <td>3</td>\n",
              "      <td>1,1,0,0</td>\n",
              "      <td>4,6,7,10</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>272 rows × 13 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     strain_name locus_tag  gene_loc  gene_strand  sgrna_strand  sgrna_loc  \\\n",
              "334  NC_003888.3   SCO5090   5532706            1            -1         32   \n",
              "330  NC_003888.3   SCO5089   5532449            1             1         61   \n",
              "329  NC_003888.3   SCO5089   5532449            1             1         65   \n",
              "328  NC_003888.3   SCO5089   5532449            1             1         66   \n",
              "326  NC_003888.3   SCO5089   5532449            1             1         80   \n",
              "..           ...       ...       ...          ...           ...        ...   \n",
              "108  NC_003888.3   SCO5087   5529801            1            -1       1038   \n",
              "295  NC_003888.3   SCO5089   5532449            1            -1         60   \n",
              "449  NC_003888.3   SCO5090   5532706            1             1        890   \n",
              "191  NC_003888.3   SCO5087   5529801            1             1        838   \n",
              "200  NC_003888.3   SCO5087   5529801            1             1        706   \n",
              "\n",
              "       gc  pam                 sgrna sgrna_seed_sequence  off_target_count  \\\n",
              "334  0.65  CGG  TGGACCACCCGGTGTTCTCC       CCCGGTGTTCTCC                 0   \n",
              "330  0.70  CGG  CGTGGAGTGCGCCGGTGAGA       TGCGCCGGTGAGA                 0   \n",
              "329  0.70  CGG  GAGTGCGCCGGTGAGACGGA       CCGGTGAGACGGA                 0   \n",
              "328  0.70  GGG  AGTGCGCCGGTGAGACGGAC       CGGTGAGACGGAC                 0   \n",
              "326  0.70  CGG  ACGGACGGGACGGACCTGTC       GGACGGACCTGTC                 0   \n",
              "..    ...  ...                   ...                 ...               ...   \n",
              "108  0.70  GGG  GATGTCCGTCGCGTCCGTGC       GTCGCGTCCGTGC                 2   \n",
              "295  0.70  GGG  CTCACCGGCGCACTCCACGA       GCGCACTCCACGA                 2   \n",
              "449  0.65  CGG  ACCCATCTGCGCGAGGTGCT       TGCGCGAGGTGCT                 3   \n",
              "191  0.70  TGG  TACGCGGGACGGCTTCGTGC       GACGGCTTCGTGC                 3   \n",
              "200  0.65  CGG  CAGCGCCGACGTGATGTTCG       GACGTGATGTTCG                 3   \n",
              "\n",
              "    editing_context editable_cytosines  \n",
              "334       0,0,0,0,0         5,6,8,9,10  \n",
              "330               1                 10  \n",
              "329           1,1,0              6,8,9  \n",
              "328           1,1,0              5,7,8  \n",
              "326               0                  6  \n",
              "..              ...                ...  \n",
              "108           0,0,0             6,7,10  \n",
              "295         0,0,0,1            3,5,6,9  \n",
              "449         0,0,0,1           3,4,7,10  \n",
              "191           0,1,0             3,5,10  \n",
              "200         1,1,0,0           4,6,7,10  \n",
              "\n",
              "[272 rows x 13 columns]"
            ]
          },
          "execution_count": 6,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "\n",
        "gene_sequences = process_specified_gene_sequences_from_record(genome, genes_to_KO)\n",
        "genes_to_KO_dict = {locus_tag: gene_sequences[locus_tag] for locus_tag in genes_to_KO if locus_tag in gene_sequences}\n",
        "\n",
        "# Identify and annotate base editing sites\n",
        "sgrna_df_with_editing = identify_base_editing_sites(sgrna_df)\n",
        "\n",
        "filtered_sgrna_df_for_base_editing = filter_sgrnas_for_base_editing(sgrna_df_with_editing)\n",
        "filtered_sgrna_df_for_base_editing"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>strain_name</th>\n",
              "      <th>locus_tag</th>\n",
              "      <th>gene_loc</th>\n",
              "      <th>gene_strand</th>\n",
              "      <th>sgrna_strand</th>\n",
              "      <th>sgrna_loc</th>\n",
              "      <th>gc</th>\n",
              "      <th>pam</th>\n",
              "      <th>sgrna</th>\n",
              "      <th>sgrna_seed_sequence</th>\n",
              "      <th>off_target_count</th>\n",
              "      <th>editing_context</th>\n",
              "      <th>editable_cytosines</th>\n",
              "      <th>mutations</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>334</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5090</td>\n",
              "      <td>5532706</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>32</td>\n",
              "      <td>0.65</td>\n",
              "      <td>CGG</td>\n",
              "      <td>TGGACCACCCGGTGTTCTCC</td>\n",
              "      <td>CCCGGTGTTCTCC</td>\n",
              "      <td>0</td>\n",
              "      <td>0,0,0,0,0</td>\n",
              "      <td>5,6,8,9,10</td>\n",
              "      <td>R8Q, V9I, V10I</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>325</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5089</td>\n",
              "      <td>5532449</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>106</td>\n",
              "      <td>0.65</td>\n",
              "      <td>AGG</td>\n",
              "      <td>CTTCCTCGACCTCCGCTTCG</td>\n",
              "      <td>GACCTCCGCTTCG</td>\n",
              "      <td>0</td>\n",
              "      <td>0,0,0,0</td>\n",
              "      <td>4,5,7,10</td>\n",
              "      <td>L31F</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>322</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5089</td>\n",
              "      <td>5532449</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>136</td>\n",
              "      <td>0.65</td>\n",
              "      <td>TGG</td>\n",
              "      <td>GTACGACTCGCTCGCCCTGA</td>\n",
              "      <td>TCGCTCGCCCTGA</td>\n",
              "      <td>0</td>\n",
              "      <td>0,0,0</td>\n",
              "      <td>4,7,9</td>\n",
              "      <td>S42L</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>318</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5089</td>\n",
              "      <td>5532449</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>194</td>\n",
              "      <td>0.65</td>\n",
              "      <td>CGG</td>\n",
              "      <td>TCCATACCCGACGACGTCGC</td>\n",
              "      <td>CCGACGACGTCGC</td>\n",
              "      <td>0</td>\n",
              "      <td>0,0,0,0</td>\n",
              "      <td>3,7,8,9</td>\n",
              "      <td>P61F</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>312</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5089</td>\n",
              "      <td>5532449</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>233</td>\n",
              "      <td>0.60</td>\n",
              "      <td>CGG</td>\n",
              "      <td>ATCAGGTCGAGCAGCTCTCG</td>\n",
              "      <td>CGAGCAGCTCTCG</td>\n",
              "      <td>0</td>\n",
              "      <td>0,0</td>\n",
              "      <td>3,8</td>\n",
              "      <td>D76N</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>534</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5090</td>\n",
              "      <td>5532706</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>140</td>\n",
              "      <td>0.65</td>\n",
              "      <td>CGG</td>\n",
              "      <td>CACGTACAGGTCCTGGAGCG</td>\n",
              "      <td>AGGTCCTGGAGCG</td>\n",
              "      <td>2</td>\n",
              "      <td>0,0</td>\n",
              "      <td>3,7</td>\n",
              "      <td>Q43*</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>78</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5087</td>\n",
              "      <td>5529801</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>745</td>\n",
              "      <td>0.65</td>\n",
              "      <td>GGG</td>\n",
              "      <td>CGACGACGATCGGGGTGATC</td>\n",
              "      <td>GATCGGGGTGATC</td>\n",
              "      <td>2</td>\n",
              "      <td>0,0</td>\n",
              "      <td>4,7</td>\n",
              "      <td>V247I, V248I</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>478</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5090</td>\n",
              "      <td>5532706</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>586</td>\n",
              "      <td>0.65</td>\n",
              "      <td>CGG</td>\n",
              "      <td>GGTGACACTCACCGAGGAGG</td>\n",
              "      <td>CTCACCGAGGAGG</td>\n",
              "      <td>2</td>\n",
              "      <td>0,0,0</td>\n",
              "      <td>6,8,10</td>\n",
              "      <td>T191I, L192F</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>335</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5090</td>\n",
              "      <td>5532706</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>43</td>\n",
              "      <td>0.65</td>\n",
              "      <td>CGG</td>\n",
              "      <td>TCCTCAGGGTGTGGACCACC</td>\n",
              "      <td>GGTGTGGACCACC</td>\n",
              "      <td>2</td>\n",
              "      <td>0,0</td>\n",
              "      <td>3,5</td>\n",
              "      <td>R14K</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>108</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5087</td>\n",
              "      <td>5529801</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>1038</td>\n",
              "      <td>0.70</td>\n",
              "      <td>GGG</td>\n",
              "      <td>GATGTCCGTCGCGTCCGTGC</td>\n",
              "      <td>GTCGCGTCCGTGC</td>\n",
              "      <td>2</td>\n",
              "      <td>0,0,0</td>\n",
              "      <td>6,7,10</td>\n",
              "      <td>D345N</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>112 rows × 14 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     strain_name locus_tag  gene_loc  gene_strand  sgrna_strand  sgrna_loc  \\\n",
              "334  NC_003888.3   SCO5090   5532706            1            -1         32   \n",
              "325  NC_003888.3   SCO5089   5532449            1             1        106   \n",
              "322  NC_003888.3   SCO5089   5532449            1             1        136   \n",
              "318  NC_003888.3   SCO5089   5532449            1             1        194   \n",
              "312  NC_003888.3   SCO5089   5532449            1            -1        233   \n",
              "..           ...       ...       ...          ...           ...        ...   \n",
              "534  NC_003888.3   SCO5090   5532706            1             1        140   \n",
              "78   NC_003888.3   SCO5087   5529801            1            -1        745   \n",
              "478  NC_003888.3   SCO5090   5532706            1             1        586   \n",
              "335  NC_003888.3   SCO5090   5532706            1            -1         43   \n",
              "108  NC_003888.3   SCO5087   5529801            1            -1       1038   \n",
              "\n",
              "       gc  pam                 sgrna sgrna_seed_sequence  off_target_count  \\\n",
              "334  0.65  CGG  TGGACCACCCGGTGTTCTCC       CCCGGTGTTCTCC                 0   \n",
              "325  0.65  AGG  CTTCCTCGACCTCCGCTTCG       GACCTCCGCTTCG                 0   \n",
              "322  0.65  TGG  GTACGACTCGCTCGCCCTGA       TCGCTCGCCCTGA                 0   \n",
              "318  0.65  CGG  TCCATACCCGACGACGTCGC       CCGACGACGTCGC                 0   \n",
              "312  0.60  CGG  ATCAGGTCGAGCAGCTCTCG       CGAGCAGCTCTCG                 0   \n",
              "..    ...  ...                   ...                 ...               ...   \n",
              "534  0.65  CGG  CACGTACAGGTCCTGGAGCG       AGGTCCTGGAGCG                 2   \n",
              "78   0.65  GGG  CGACGACGATCGGGGTGATC       GATCGGGGTGATC                 2   \n",
              "478  0.65  CGG  GGTGACACTCACCGAGGAGG       CTCACCGAGGAGG                 2   \n",
              "335  0.65  CGG  TCCTCAGGGTGTGGACCACC       GGTGTGGACCACC                 2   \n",
              "108  0.70  GGG  GATGTCCGTCGCGTCCGTGC       GTCGCGTCCGTGC                 2   \n",
              "\n",
              "    editing_context editable_cytosines       mutations  \n",
              "334       0,0,0,0,0         5,6,8,9,10  R8Q, V9I, V10I  \n",
              "325         0,0,0,0           4,5,7,10            L31F  \n",
              "322           0,0,0              4,7,9            S42L  \n",
              "318         0,0,0,0            3,7,8,9            P61F  \n",
              "312             0,0                3,8            D76N  \n",
              "..              ...                ...             ...  \n",
              "534             0,0                3,7            Q43*  \n",
              "78              0,0                4,7    V247I, V248I  \n",
              "478           0,0,0             6,8,10    T191I, L192F  \n",
              "335             0,0                3,5            R14K  \n",
              "108           0,0,0             6,7,10           D345N  \n",
              "\n",
              "[112 rows x 14 columns]"
            ]
          },
          "execution_count": 7,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "\n",
        "# Process the DataFrame to apply C-to-T mutations\n",
        "mutated_sgrna_df = process_base_editing(filtered_sgrna_df_for_base_editing, genes_to_KO_dict, only_stop_codons = False)\n",
        "mutated_sgrna_df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {},
      "outputs": [
        {
          "data": {
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              "  <thead>\n",
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              "      <th></th>\n",
              "      <th>strain_name</th>\n",
              "      <th>locus_tag</th>\n",
              "      <th>gene_loc</th>\n",
              "      <th>gene_strand</th>\n",
              "      <th>sgrna_strand</th>\n",
              "      <th>sgrna_loc</th>\n",
              "      <th>gc</th>\n",
              "      <th>pam</th>\n",
              "      <th>sgrna</th>\n",
              "      <th>sgrna_seed_sequence</th>\n",
              "      <th>off_target_count</th>\n",
              "      <th>editing_context</th>\n",
              "      <th>editable_cytosines</th>\n",
              "      <th>mutations</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>534</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5090</td>\n",
              "      <td>5532706</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>140</td>\n",
              "      <td>0.65</td>\n",
              "      <td>CGG</td>\n",
              "      <td>CACGTACAGGTCCTGGAGCG</td>\n",
              "      <td>AGGTCCTGGAGCG</td>\n",
              "      <td>2</td>\n",
              "      <td>0,0</td>\n",
              "      <td>3,7</td>\n",
              "      <td>Q43*</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>319</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5089</td>\n",
              "      <td>5532449</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>167</td>\n",
              "      <td>0.70</td>\n",
              "      <td>CGG</td>\n",
              "      <td>GCGCGACTCGAGAGCCGGTA</td>\n",
              "      <td>TCGAGAGCCGGTA</td>\n",
              "      <td>0</td>\n",
              "      <td>1,0,0</td>\n",
              "      <td>4,7,9</td>\n",
              "      <td>R51*, L52F</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>352</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5090</td>\n",
              "      <td>5532706</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>174</td>\n",
              "      <td>0.65</td>\n",
              "      <td>CGG</td>\n",
              "      <td>CGCCCAGATCCGGAAGCGTT</td>\n",
              "      <td>ATCCGGAAGCGTT</td>\n",
              "      <td>0</td>\n",
              "      <td>1,0,0,0</td>\n",
              "      <td>3,4,5,10</td>\n",
              "      <td>W57*, A58T</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>354</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5090</td>\n",
              "      <td>5532706</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>208</td>\n",
              "      <td>0.65</td>\n",
              "      <td>CGG</td>\n",
              "      <td>GGGACGTCCAGGTCTTCACC</td>\n",
              "      <td>CCAGGTCTTCACC</td>\n",
              "      <td>0</td>\n",
              "      <td>0,0,0</td>\n",
              "      <td>5,8,9</td>\n",
              "      <td>W67*</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5087</td>\n",
              "      <td>5529801</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>210</td>\n",
              "      <td>0.60</td>\n",
              "      <td>GGG</td>\n",
              "      <td>GAGCAGTTCCCAGAACTGCC</td>\n",
              "      <td>TCCCAGAACTGCC</td>\n",
              "      <td>0</td>\n",
              "      <td>1,0,0</td>\n",
              "      <td>4,9,10</td>\n",
              "      <td>W67*, E68K</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>54</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5087</td>\n",
              "      <td>5529801</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>522</td>\n",
              "      <td>0.70</td>\n",
              "      <td>CGG</td>\n",
              "      <td>GTCGACCTCCCAGTCACGGC</td>\n",
              "      <td>TCCCAGTCACGGC</td>\n",
              "      <td>0</td>\n",
              "      <td>0,0,0,0,0</td>\n",
              "      <td>3,6,7,9,10</td>\n",
              "      <td>W171*, E172K, V173I, D174N</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>471</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5090</td>\n",
              "      <td>5532706</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>640</td>\n",
              "      <td>0.60</td>\n",
              "      <td>TGG</td>\n",
              "      <td>GACCGTCCAGGACATGACCA</td>\n",
              "      <td>CAGGACATGACCA</td>\n",
              "      <td>0</td>\n",
              "      <td>0,0,0,0</td>\n",
              "      <td>3,4,7,8</td>\n",
              "      <td>T208I, Q210*</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     strain_name locus_tag  gene_loc  gene_strand  sgrna_strand  sgrna_loc  \\\n",
              "534  NC_003888.3   SCO5090   5532706            1             1        140   \n",
              "319  NC_003888.3   SCO5089   5532449            1             1        167   \n",
              "352  NC_003888.3   SCO5090   5532706            1            -1        174   \n",
              "354  NC_003888.3   SCO5090   5532706            1            -1        208   \n",
              "17   NC_003888.3   SCO5087   5529801            1            -1        210   \n",
              "54   NC_003888.3   SCO5087   5529801            1            -1        522   \n",
              "471  NC_003888.3   SCO5090   5532706            1             1        640   \n",
              "\n",
              "       gc  pam                 sgrna sgrna_seed_sequence  off_target_count  \\\n",
              "534  0.65  CGG  CACGTACAGGTCCTGGAGCG       AGGTCCTGGAGCG                 2   \n",
              "319  0.70  CGG  GCGCGACTCGAGAGCCGGTA       TCGAGAGCCGGTA                 0   \n",
              "352  0.65  CGG  CGCCCAGATCCGGAAGCGTT       ATCCGGAAGCGTT                 0   \n",
              "354  0.65  CGG  GGGACGTCCAGGTCTTCACC       CCAGGTCTTCACC                 0   \n",
              "17   0.60  GGG  GAGCAGTTCCCAGAACTGCC       TCCCAGAACTGCC                 0   \n",
              "54   0.70  CGG  GTCGACCTCCCAGTCACGGC       TCCCAGTCACGGC                 0   \n",
              "471  0.60  TGG  GACCGTCCAGGACATGACCA       CAGGACATGACCA                 0   \n",
              "\n",
              "    editing_context editable_cytosines                   mutations  \n",
              "534             0,0                3,7                        Q43*  \n",
              "319           1,0,0              4,7,9                  R51*, L52F  \n",
              "352         1,0,0,0           3,4,5,10                  W57*, A58T  \n",
              "354           0,0,0              5,8,9                        W67*  \n",
              "17            1,0,0             4,9,10                  W67*, E68K  \n",
              "54        0,0,0,0,0         3,6,7,9,10  W171*, E172K, V173I, D174N  \n",
              "471         0,0,0,0            3,4,7,8                T208I, Q210*  "
            ]
          },
          "execution_count": 8,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Process the DataFrame to apply C-to-T mutations\n",
        "mutated_sgrna_df = process_base_editing(filtered_sgrna_df_for_base_editing, \n",
        "                                        genes_to_KO_dict, \n",
        "                                        only_stop_codons = True, \n",
        "                                        editing_context= False)\n",
        "mutated_sgrna_df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>strain_name</th>\n",
              "      <th>locus_tag</th>\n",
              "      <th>gene_loc</th>\n",
              "      <th>gene_strand</th>\n",
              "      <th>sgrna_strand</th>\n",
              "      <th>sgrna_loc</th>\n",
              "      <th>gc</th>\n",
              "      <th>pam</th>\n",
              "      <th>sgrna</th>\n",
              "      <th>sgrna_seed_sequence</th>\n",
              "      <th>off_target_count</th>\n",
              "      <th>editing_context</th>\n",
              "      <th>editable_cytosines</th>\n",
              "      <th>mutations</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>534</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5090</td>\n",
              "      <td>5532706</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>140</td>\n",
              "      <td>0.65</td>\n",
              "      <td>CGG</td>\n",
              "      <td>CACGTACAGGTCCTGGAGCG</td>\n",
              "      <td>AGGTCCTGGAGCG</td>\n",
              "      <td>2</td>\n",
              "      <td>0,0</td>\n",
              "      <td>3,7</td>\n",
              "      <td>Q43*</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>354</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5090</td>\n",
              "      <td>5532706</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>208</td>\n",
              "      <td>0.65</td>\n",
              "      <td>CGG</td>\n",
              "      <td>GGGACGTCCAGGTCTTCACC</td>\n",
              "      <td>CCAGGTCTTCACC</td>\n",
              "      <td>0</td>\n",
              "      <td>0,0,0</td>\n",
              "      <td>5,8,9</td>\n",
              "      <td>W67*</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>54</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5087</td>\n",
              "      <td>5529801</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>522</td>\n",
              "      <td>0.70</td>\n",
              "      <td>CGG</td>\n",
              "      <td>GTCGACCTCCCAGTCACGGC</td>\n",
              "      <td>TCCCAGTCACGGC</td>\n",
              "      <td>0</td>\n",
              "      <td>0,0,0,0,0</td>\n",
              "      <td>3,6,7,9,10</td>\n",
              "      <td>W171*, E172K, V173I, D174N</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>471</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5090</td>\n",
              "      <td>5532706</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>640</td>\n",
              "      <td>0.60</td>\n",
              "      <td>TGG</td>\n",
              "      <td>GACCGTCCAGGACATGACCA</td>\n",
              "      <td>CAGGACATGACCA</td>\n",
              "      <td>0</td>\n",
              "      <td>0,0,0,0</td>\n",
              "      <td>3,4,7,8</td>\n",
              "      <td>T208I, Q210*</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     strain_name locus_tag  gene_loc  gene_strand  sgrna_strand  sgrna_loc  \\\n",
              "534  NC_003888.3   SCO5090   5532706            1             1        140   \n",
              "354  NC_003888.3   SCO5090   5532706            1            -1        208   \n",
              "54   NC_003888.3   SCO5087   5529801            1            -1        522   \n",
              "471  NC_003888.3   SCO5090   5532706            1             1        640   \n",
              "\n",
              "       gc  pam                 sgrna sgrna_seed_sequence  off_target_count  \\\n",
              "534  0.65  CGG  CACGTACAGGTCCTGGAGCG       AGGTCCTGGAGCG                 2   \n",
              "354  0.65  CGG  GGGACGTCCAGGTCTTCACC       CCAGGTCTTCACC                 0   \n",
              "54   0.70  CGG  GTCGACCTCCCAGTCACGGC       TCCCAGTCACGGC                 0   \n",
              "471  0.60  TGG  GACCGTCCAGGACATGACCA       CAGGACATGACCA                 0   \n",
              "\n",
              "    editing_context editable_cytosines                   mutations  \n",
              "534             0,0                3,7                        Q43*  \n",
              "354           0,0,0              5,8,9                        W67*  \n",
              "54        0,0,0,0,0         3,6,7,9,10  W171*, E172K, V173I, D174N  \n",
              "471         0,0,0,0            3,4,7,8                T208I, Q210*  "
            ]
          },
          "execution_count": 9,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Process the DataFrame to apply C-to-T mutations\n",
        "mutated_sgrna_df = process_base_editing(filtered_sgrna_df_for_base_editing, \n",
        "                                        genes_to_KO_dict, \n",
        "                                        only_stop_codons = True, \n",
        "                                        editing_context= True)\n",
        "mutated_sgrna_df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
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              "<style scoped>\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>strain_name</th>\n",
              "      <th>locus_tag</th>\n",
              "      <th>gene_loc</th>\n",
              "      <th>gene_strand</th>\n",
              "      <th>sgrna_strand</th>\n",
              "      <th>sgrna_loc</th>\n",
              "      <th>gc</th>\n",
              "      <th>pam</th>\n",
              "      <th>sgrna</th>\n",
              "      <th>sgrna_seed_sequence</th>\n",
              "      <th>off_target_count</th>\n",
              "      <th>editing_context</th>\n",
              "      <th>editable_cytosines</th>\n",
              "      <th>mutations</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>534</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5090</td>\n",
              "      <td>5532706</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>140</td>\n",
              "      <td>0.65</td>\n",
              "      <td>CGG</td>\n",
              "      <td>CACGTACAGGTCCTGGAGCG</td>\n",
              "      <td>AGGTCCTGGAGCG</td>\n",
              "      <td>2</td>\n",
              "      <td>0,0</td>\n",
              "      <td>3,7</td>\n",
              "      <td>Q43*</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>354</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5090</td>\n",
              "      <td>5532706</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>208</td>\n",
              "      <td>0.65</td>\n",
              "      <td>CGG</td>\n",
              "      <td>GGGACGTCCAGGTCTTCACC</td>\n",
              "      <td>CCAGGTCTTCACC</td>\n",
              "      <td>0</td>\n",
              "      <td>0,0,0</td>\n",
              "      <td>5,8,9</td>\n",
              "      <td>W67*</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>54</th>\n",
              "      <td>NC_003888.3</td>\n",
              "      <td>SCO5087</td>\n",
              "      <td>5529801</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>522</td>\n",
              "      <td>0.70</td>\n",
              "      <td>CGG</td>\n",
              "      <td>GTCGACCTCCCAGTCACGGC</td>\n",
              "      <td>TCCCAGTCACGGC</td>\n",
              "      <td>0</td>\n",
              "      <td>0,0,0,0,0</td>\n",
              "      <td>3,6,7,9,10</td>\n",
              "      <td>W171*, E172K, V173I, D174N</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     strain_name locus_tag  gene_loc  gene_strand  sgrna_strand  sgrna_loc  \\\n",
              "534  NC_003888.3   SCO5090   5532706            1             1        140   \n",
              "354  NC_003888.3   SCO5090   5532706            1            -1        208   \n",
              "54   NC_003888.3   SCO5087   5529801            1            -1        522   \n",
              "\n",
              "       gc  pam                 sgrna sgrna_seed_sequence  off_target_count  \\\n",
              "534  0.65  CGG  CACGTACAGGTCCTGGAGCG       AGGTCCTGGAGCG                 2   \n",
              "354  0.65  CGG  GGGACGTCCAGGTCTTCACC       CCAGGTCTTCACC                 0   \n",
              "54   0.70  CGG  GTCGACCTCCCAGTCACGGC       TCCCAGTCACGGC                 0   \n",
              "\n",
              "    editing_context editable_cytosines                   mutations  \n",
              "534             0,0                3,7                        Q43*  \n",
              "354           0,0,0              5,8,9                        W67*  \n",
              "54        0,0,0,0,0         3,6,7,9,10  W171*, E172K, V173I, D174N  "
            ]
          },
          "execution_count": 10,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Filter the DataFrame to retain only up to 5 sgRNA sequences per locus_tag\n",
        "filtered_df = mutated_sgrna_df.groupby('locus_tag').head(number_of_sgRNAs_per_group)\n",
        "filtered_df"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Output"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[Dseqrecord(-20), Dseqrecord(-20), Dseqrecord(-20)]"
            ]
          },
          "execution_count": 11,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "sgRNA_list = dataframe_to_seqrecords(filtered_df)\n",
        "sgRNA_list"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {},
      "outputs": [],
      "source": [
        "sgRNA_handle_cys4_sites = sgRNA_handle_cys4_site*len(sgRNA_list)\n",
        "\n",
        "golden_gate = GoldenGateCloning(sgRNA_list,\n",
        "                                sgRNA_handle_cys4_sites, \n",
        "                                target_tm= melting_temperature,\n",
        "                                restriction_overhang_f = restriction_overhang_f,\n",
        "                                restriction_overhang_r = restriction_overhang_r,\n",
        "                                backbone_overhang_f = backbone_overhang_f,\n",
        "                                backbone_overhang_r = backbone_overhang_r,\n",
        "                                cys4 = cys4,\n",
        "                                tm_function = primer_tm_neb, \n",
        "                                polymerase = chosen_polymerase ) "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Locus Tag</th>\n",
              "      <th>f_primer_name</th>\n",
              "      <th>r_primer_name</th>\n",
              "      <th>f_primer_sequences(5-3)</th>\n",
              "      <th>r_primer_sequences(5-3)</th>\n",
              "      <th>f_tm</th>\n",
              "      <th>r_tm</th>\n",
              "      <th>ta</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>sgRNA_handle_cys4</td>\n",
              "      <td>fwd_primer_SCO5090_140</td>\n",
              "      <td>rev_primer_SCO5090_140</td>\n",
              "      <td>GATCGGGTCTCCCATGGTTCACTGCCGTATAGGCAGCTAAGAAACA...</td>\n",
              "      <td>GATCAGGTCTCGTCCCAAAAAAGCACCGACTCG</td>\n",
              "      <td>56</td>\n",
              "      <td>54</td>\n",
              "      <td>58</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>sgRNA_handle_cys4</td>\n",
              "      <td>fwd_primer_SCO5090_208</td>\n",
              "      <td>rev_primer_SCO5090_208</td>\n",
              "      <td>GATCGGGTCTCCGGGACGTCCAGGTCTTCACCGTTTTAGAGCTAGA...</td>\n",
              "      <td>GATCAGGTCTCGCGACAAAAAAGCACCGACTCG</td>\n",
              "      <td>56</td>\n",
              "      <td>54</td>\n",
              "      <td>58</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>sgRNA_handle_cys4</td>\n",
              "      <td>fwd_primer_SCO5087_522</td>\n",
              "      <td>rev_primer_SCO5087_522</td>\n",
              "      <td>GATCGGGTCTCCGTCGACCTCCCAGTCACGGCGTTTTAGAGCTAGA...</td>\n",
              "      <td>GATCAGGTCTCGCTAGAAAAAAGCACCGACTCG</td>\n",
              "      <td>56</td>\n",
              "      <td>54</td>\n",
              "      <td>58</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           Locus Tag           f_primer_name           r_primer_name  \\\n",
              "0  sgRNA_handle_cys4  fwd_primer_SCO5090_140  rev_primer_SCO5090_140   \n",
              "1  sgRNA_handle_cys4  fwd_primer_SCO5090_208  rev_primer_SCO5090_208   \n",
              "2  sgRNA_handle_cys4  fwd_primer_SCO5087_522  rev_primer_SCO5087_522   \n",
              "\n",
              "                             f_primer_sequences(5-3)  \\\n",
              "0  GATCGGGTCTCCCATGGTTCACTGCCGTATAGGCAGCTAAGAAACA...   \n",
              "1  GATCGGGTCTCCGGGACGTCCAGGTCTTCACCGTTTTAGAGCTAGA...   \n",
              "2  GATCGGGTCTCCGTCGACCTCCCAGTCACGGCGTTTTAGAGCTAGA...   \n",
              "\n",
              "             r_primer_sequences(5-3)  f_tm  r_tm  ta  \n",
              "0  GATCAGGTCTCGTCCCAAAAAAGCACCGACTCG    56    54  58  \n",
              "1  GATCAGGTCTCGCGACAAAAAAGCACCGACTCG    56    54  58  \n",
              "2  GATCAGGTCTCGCTAGAAAAAAGCACCGACTCG    56    54  58  "
            ]
          },
          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "primer_df = golden_gate.generate_primer_dataframe()\n",
        "primer_df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Skipping analysis for primer pair fwd_primer_SCO5090_140 & rev_primer_SCO5090_140 due to length constraints.\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>annealing_temperature</th>\n",
              "      <th>primer_pair</th>\n",
              "      <th>homodimer_forward_tm</th>\n",
              "      <th>homodimer_forward_deltaG (kcal/mol)</th>\n",
              "      <th>homodimer_reverse_tm</th>\n",
              "      <th>homodimer_reverse_deltaG (kcal/mol)</th>\n",
              "      <th>heterodimer_tm</th>\n",
              "      <th>heterodimer_deltaG (kcal/mol)</th>\n",
              "      <th>hairpin_forward_structure_found</th>\n",
              "      <th>hairpin_forward_tm</th>\n",
              "      <th>hairpin_forward_deltaG (kcal/mol)</th>\n",
              "      <th>hairpin_reverse_structure_found</th>\n",
              "      <th>hairpin_reverse_tm</th>\n",
              "      <th>hairpin_reverse_deltaG (kcal/mol)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>58</td>\n",
              "      <td>fwd_primer_SCO5090_208 &amp; rev_primer_SCO5090_208</td>\n",
              "      <td>38.497138</td>\n",
              "      <td>-1.774563</td>\n",
              "      <td>3.710596</td>\n",
              "      <td>-3.582472</td>\n",
              "      <td>10.978173</td>\n",
              "      <td>1.893397</td>\n",
              "      <td>True</td>\n",
              "      <td>59.149103</td>\n",
              "      <td>-0.053945</td>\n",
              "      <td>False</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>58</td>\n",
              "      <td>fwd_primer_SCO5087_522 &amp; rev_primer_SCO5087_522</td>\n",
              "      <td>25.023322</td>\n",
              "      <td>7.202194</td>\n",
              "      <td>-14.334752</td>\n",
              "      <td>-1.634182</td>\n",
              "      <td>16.105063</td>\n",
              "      <td>3.290762</td>\n",
              "      <td>True</td>\n",
              "      <td>53.974837</td>\n",
              "      <td>0.348222</td>\n",
              "      <td>False</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   annealing_temperature                                      primer_pair  \\\n",
              "0                     58  fwd_primer_SCO5090_208 & rev_primer_SCO5090_208   \n",
              "1                     58  fwd_primer_SCO5087_522 & rev_primer_SCO5087_522   \n",
              "\n",
              "   homodimer_forward_tm  homodimer_forward_deltaG (kcal/mol)  \\\n",
              "0             38.497138                            -1.774563   \n",
              "1             25.023322                             7.202194   \n",
              "\n",
              "   homodimer_reverse_tm  homodimer_reverse_deltaG (kcal/mol)  heterodimer_tm  \\\n",
              "0              3.710596                            -3.582472       10.978173   \n",
              "1            -14.334752                            -1.634182       16.105063   \n",
              "\n",
              "   heterodimer_deltaG (kcal/mol)  hairpin_forward_structure_found  \\\n",
              "0                       1.893397                             True   \n",
              "1                       3.290762                             True   \n",
              "\n",
              "   hairpin_forward_tm  hairpin_forward_deltaG (kcal/mol)  \\\n",
              "0           59.149103                          -0.053945   \n",
              "1           53.974837                           0.348222   \n",
              "\n",
              "   hairpin_reverse_structure_found  hairpin_reverse_tm  \\\n",
              "0                            False                 0.0   \n",
              "1                            False                 0.0   \n",
              "\n",
              "   hairpin_reverse_deltaG (kcal/mol)  \n",
              "0                                0.0  \n",
              "1                                0.0  "
            ]
          },
          "execution_count": 14,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Primer analysis\n",
        "analysis_of_primers = analyze_primers_and_hairpins(primer_df)\n",
        "analysis_of_primers"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Name</th>\n",
              "      <th>Sequence</th>\n",
              "      <th>Concentration</th>\n",
              "      <th>Purification</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>fwd_primer_SCO5090_140</td>\n",
              "      <td>GATCGGGTCTCCCATGGTTCACTGCCGTATAGGCAGCTAAGAAACA...</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>fwd_primer_SCO5090_208</td>\n",
              "      <td>GATCGGGTCTCCGGGACGTCCAGGTCTTCACCGTTTTAGAGCTAGA...</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>fwd_primer_SCO5087_522</td>\n",
              "      <td>GATCGGGTCTCCGTCGACCTCCCAGTCACGGCGTTTTAGAGCTAGA...</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>rev_primer_SCO5090_140</td>\n",
              "      <td>GATCAGGTCTCGTCCCAAAAAAGCACCGACTCG</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>rev_primer_SCO5090_208</td>\n",
              "      <td>GATCAGGTCTCGCGACAAAAAAGCACCGACTCG</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>rev_primer_SCO5087_522</td>\n",
              "      <td>GATCAGGTCTCGCTAGAAAAAAGCACCGACTCG</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                     Name                                           Sequence  \\\n",
              "0  fwd_primer_SCO5090_140  GATCGGGTCTCCCATGGTTCACTGCCGTATAGGCAGCTAAGAAACA...   \n",
              "1  fwd_primer_SCO5090_208  GATCGGGTCTCCGGGACGTCCAGGTCTTCACCGTTTTAGAGCTAGA...   \n",
              "2  fwd_primer_SCO5087_522  GATCGGGTCTCCGTCGACCTCCCAGTCACGGCGTTTTAGAGCTAGA...   \n",
              "3  rev_primer_SCO5090_140                  GATCAGGTCTCGTCCCAAAAAAGCACCGACTCG   \n",
              "4  rev_primer_SCO5090_208                  GATCAGGTCTCGCGACAAAAAAGCACCGACTCG   \n",
              "5  rev_primer_SCO5087_522                  GATCAGGTCTCGCTAGAAAAAAGCACCGACTCG   \n",
              "\n",
              "  Concentration Purification  \n",
              "0          25nm          STD  \n",
              "1          25nm          STD  \n",
              "2          25nm          STD  \n",
              "3          25nm          STD  \n",
              "4          25nm          STD  \n",
              "5          25nm          STD  "
            ]
          },
          "execution_count": 15,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# 2 Ready made IDT format\n",
        "idt_df = create_idt_order_dataframe(primer_df, concentration=\"25nm\", purification=\"STD\")\n",
        "idt_df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {},
      "outputs": [],
      "source": [
        "list_of_amplicons = golden_gate.simulate_pcrs()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "SCO5090_140_pcr_products\n",
            "SCO5090_208_pcr_products\n",
            "SCO5087_522_pcr_products\n"
          ]
        },
        {
          "data": {
            "image/jpeg": 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",
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=300x600>"
            ]
          },
          "execution_count": 17,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "from pydna.gel import gel\n",
        "from pydna.ladders import GeneRuler_1kb_plus\n",
        "\n",
        "bands = list_of_amplicons\n",
        "for band in bands:\n",
        "    print(band.name)\n",
        "\n",
        "gel([GeneRuler_1kb_plus, *[[band] for band in bands]])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Amplicon Name</th>\n",
              "      <th>5' Overhang</th>\n",
              "      <th>5' Duplicate</th>\n",
              "      <th>3' Overhang</th>\n",
              "      <th>3' Duplicate</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Amplicon_SCO5090_140_pcr_products</td>\n",
              "      <td>CATG</td>\n",
              "      <td>No</td>\n",
              "      <td>GGGA</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Amplicon_SCO5090_208_pcr_products</td>\n",
              "      <td>GGGA</td>\n",
              "      <td>No</td>\n",
              "      <td>GTCG</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Amplicon_SCO5087_522_pcr_products</td>\n",
              "      <td>GTCG</td>\n",
              "      <td>No</td>\n",
              "      <td>CTAG</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                       Amplicon Name 5' Overhang 5' Duplicate 3' Overhang  \\\n",
              "0  Amplicon_SCO5090_140_pcr_products        CATG           No        GGGA   \n",
              "1  Amplicon_SCO5090_208_pcr_products        GGGA           No        GTCG   \n",
              "2  Amplicon_SCO5087_522_pcr_products        GTCG           No        CTAG   \n",
              "\n",
              "  3' Duplicate  \n",
              "0           No  \n",
              "1           No  \n",
              "2           No  "
            ]
          },
          "execution_count": 18,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "overhangs = create_overhang_dataframe(list_of_amplicons)\n",
        "overhangs"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Dseqrecord(-138)\n",
            "CATGGTTCACTGCCGTATAGGCAGCTAAGAAACACGTACAGGTCCTGGAGCG\u001b[48;5;11mGTTTTAGAGCTAGAAATAGCAAGT\u001b[0mTAAAATAAGGCTAGTCCGTTATCAACTTGAAAAAGTGGCACCGAGTCGGTGCTTTTTT    \n",
            "    CAAGTGACGGCATATCCGTCGATTCTTTGTGCATGTCCAGGACCTCGCCAAAATCTCGATCTTTATCGTTCAATTTTATTCCGATCAGGCAATAGTTGAACTTTTTCACCGTGGCTCAGCCACGAAAAAACCCT\n",
            "Dseqrecord(-106)\n",
            "GGGACGTCCAGGTCTTCACC\u001b[48;5;11mGTTTTAGAGCTAGAAATAGCAAGT\u001b[0mTAAAATAAGGCTAGTCCGTTATCAACTTGAAAAAGTGGCACCGAGTCGGTGCTTTTTT    \n",
            "    GCAGGTCCAGAAGTGGCAAAATCTCGATCTTTATCGTTCAATTTTATTCCGATCAGGCAATAGTTGAACTTTTTCACCGTGGCTCAGCCACGAAAAAACAGC\n",
            "Dseqrecord(-106)\n",
            "GTCGACCTCCCAGTCACGGC\u001b[48;5;11mGTTTTAGAGCTAGAAATAGCAAGT\u001b[0mTAAAATAAGGCTAGTCCGTTATCAACTTGAAAAAGTGGCACCGAGTCGGTGCTTTTTT    \n",
            "    TGGAGGGTCAGTGCCGCAAAATCTCGATCTTTATCGTTCAATTTTATTCCGATCAGGCAATAGTTGAACTTTTTCACCGTGGCTCAGCCACGAAAAAAGATC\n"
          ]
        }
      ],
      "source": [
        "digest_amplicons = digest_amplicons_w_BsaI(list_of_amplicons)\n",
        "for digest in digest_amplicons: \n",
        "    print(digest.figure())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[Dseqrecord(-138), Dseqrecord(-106), Dseqrecord(-106)]"
            ]
          },
          "execution_count": 20,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "digest_amplicons"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Successfully looped the plasmid.\n"
          ]
        }
      ],
      "source": [
        "\n",
        "from Bio.Restriction import NcoI, NheI\n",
        "\n",
        "try:\n",
        "    linear_plasmid, smaller_frag = sorted(clean_plasmid.cut(NcoI, NheI), key=lambda x: len(x), reverse=True)\n",
        "    for i in range(len(digest_amplicons)):\n",
        "        # Assuming digest_amplicons[i] is a Dseqrecord, concatenate Dseq sequences\n",
        "        linear_plasmid.seq += digest_amplicons[i].seq\n",
        "    \n",
        "    try:\n",
        "        rec_vec = linear_plasmid.looped()\n",
        "        print(\"Successfully looped the plasmid.\")\n",
        "    except Exception as e:\n",
        "        print(f\"An error occurred while trying to loop the plasmid: {e}\")\n",
        "        # Handle the error or provide an alternative action here\n",
        "        rec_vec = None  # Example response; adjust as needed\n",
        "\n",
        "except Exception as e:\n",
        "    print(f\"An error occurred during plasmid digestion or preparation: {e}\")\n",
        "    # Additional error handling or cleanup here\n",
        "    rec_vec = None  # Ensure rec_vec is defined even if an error occurs"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'pCRISPR-mcBEST_3_sgrnas'"
            ]
          },
          "execution_count": 22,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Constructing a meaningful name, ID, and description for the assembled plasmid using user input\n",
        "plasmid_components = \"_\".join(genes_to_KO)  # Concatenates gene names from the user's list\n",
        "plasmid_purpose = f\"pCRISPR-mcBEST_{len(filtered_df)}_sgrnas\"  # Example: purpose of the plasmid\n",
        "\n",
        "rec_vec.name = f'{plasmid_purpose}'#_{plasmid_components}'\n",
        "rec_vec.id = rec_vec.name  # Using the same value for ID as for name for simplicity\n",
        "rec_vec.description = f'CRISPR-mcBEST_plasmid {\", \".join(genes_to_KO)} for gene KNOCK-DOWN, assembled using StreptoCAD.'\n",
        "rec_vec.id"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Dseqrecord(o12802)"
            ]
          },
          "execution_count": 23,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# annotate the plasmid correctly\n",
        "annotate_plasmid_with_sgrnas(rec_vec, filtered_df)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {},
      "outputs": [],
      "source": [
        "print_plasmid = False\n",
        "\n",
        "if print_plasmid: \n",
        "    rec_vec.write(f\"../../data/plasmids/sgRNA_plasmids_pCRISPR_mcBEST/{rec_vec.id}.gb\")\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Dseqrecord(o12802)"
            ]
          },
          "execution_count": 25,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "rec_vec"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'sgRNA_SCO5090(140)_sgRNA_SCO5090(208)_sgRNA_SCO5087(522)_'"
            ]
          },
          "execution_count": 26,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "integration_names = filtered_df.apply(lambda row: f\"sgRNA_{row['locus_tag']}({row['sgrna_loc']})_\", axis=1).tolist()\n",
        "integration_names = ''.join(integration_names)\n",
        "integration_names"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>plasmid_name</th>\n",
              "      <th>date</th>\n",
              "      <th>original_plasmid</th>\n",
              "      <th>integration</th>\n",
              "      <th>size</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>pCRISPR-mcBEST_3_sgrnas</td>\n",
              "      <td>2024-10-25</td>\n",
              "      <td>pCRISPR-mcBEST</td>\n",
              "      <td>sgRNA_SCO5090(140);sgRNA_SCO5090(208);sgRNA_SC...</td>\n",
              "      <td>12802</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              plasmid_name        date original_plasmid  \\\n",
              "0  pCRISPR-mcBEST_3_sgrnas  2024-10-25   pCRISPR-mcBEST   \n",
              "\n",
              "                                         integration   size  \n",
              "0  sgRNA_SCO5090(140);sgRNA_SCO5090(208);sgRNA_SC...  12802  "
            ]
          },
          "execution_count": 27,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "integration_names = filtered_df.apply(lambda row: f\"sgRNA_{row['locus_tag']}({row['sgrna_loc']})\", axis=1).tolist()\n",
        "integration_names = [';'.join(integration_names)]\n",
        "\n",
        "plasmid_metadata_df = extract_metadata_to_dataframe([rec_vec],\n",
        "                                                    clean_plasmid,\n",
        "                                                    integration_names)\n",
        "\n",
        "plasmid_metadata_df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {},
      "outputs": [],
      "source": [
        "pd.set_option('display.max_columns', None)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 29,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>locus tag</th>\n",
              "      <th>f_primer_name</th>\n",
              "      <th>r_primer_name</th>\n",
              "      <th>f_primer_sequences(5-3)</th>\n",
              "      <th>r_primer_sequences(5-3)</th>\n",
              "      <th>f_tm</th>\n",
              "      <th>r_tm</th>\n",
              "      <th>ta</th>\n",
              "      <th>flanking_region</th>\n",
              "      <th>annealing_temperature</th>\n",
              "      <th>primer_pair</th>\n",
              "      <th>homodimer_forward_tm</th>\n",
              "      <th>homodimer_forward_deltaG (kcal/mol)</th>\n",
              "      <th>homodimer_reverse_tm</th>\n",
              "      <th>homodimer_reverse_deltaG (kcal/mol)</th>\n",
              "      <th>heterodimer_tm</th>\n",
              "      <th>heterodimer_deltaG (kcal/mol)</th>\n",
              "      <th>hairpin_forward_structure_found</th>\n",
              "      <th>hairpin_forward_tm</th>\n",
              "      <th>hairpin_forward_deltaG (kcal/mol)</th>\n",
              "      <th>hairpin_reverse_structure_found</th>\n",
              "      <th>hairpin_reverse_tm</th>\n",
              "      <th>hairpin_reverse_deltaG (kcal/mol)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>SCO5087</td>\n",
              "      <td>SCO5087_fwd_checking_primer</td>\n",
              "      <td>SCO5087_rev_checking_primer</td>\n",
              "      <td>TAGGGCGCGGC</td>\n",
              "      <td>CCGGAGACCACCAG</td>\n",
              "      <td>51</td>\n",
              "      <td>53</td>\n",
              "      <td>55</td>\n",
              "      <td>550</td>\n",
              "      <td>55</td>\n",
              "      <td>SCO5087_fwd_checking_primer &amp; SCO5087_rev_chec...</td>\n",
              "      <td>26.385240</td>\n",
              "      <td>-5.886397</td>\n",
              "      <td>-15.268430</td>\n",
              "      <td>-3.528618</td>\n",
              "      <td>-34.382170</td>\n",
              "      <td>-1.534614</td>\n",
              "      <td>False</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>False</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>SCO5089</td>\n",
              "      <td>SCO5089_fwd_checking_primer</td>\n",
              "      <td>SCO5089_rev_checking_primer</td>\n",
              "      <td>CCCTTCGACGAGCG</td>\n",
              "      <td>CGGGGCCGGT</td>\n",
              "      <td>54</td>\n",
              "      <td>49</td>\n",
              "      <td>53</td>\n",
              "      <td>600</td>\n",
              "      <td>53</td>\n",
              "      <td>SCO5089_fwd_checking_primer &amp; SCO5089_rev_chec...</td>\n",
              "      <td>-5.338917</td>\n",
              "      <td>-1.468854</td>\n",
              "      <td>1.902964</td>\n",
              "      <td>-3.360252</td>\n",
              "      <td>-36.526236</td>\n",
              "      <td>-1.541041</td>\n",
              "      <td>False</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>False</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>SCO5090</td>\n",
              "      <td>SCO5090_fwd_checking_primer</td>\n",
              "      <td>SCO5090_rev_checking_primer</td>\n",
              "      <td>CGAGCTGGACGCC</td>\n",
              "      <td>CGACGACCACCTCG</td>\n",
              "      <td>54</td>\n",
              "      <td>54</td>\n",
              "      <td>58</td>\n",
              "      <td>600</td>\n",
              "      <td>58</td>\n",
              "      <td>SCO5090_fwd_checking_primer &amp; SCO5090_rev_chec...</td>\n",
              "      <td>-27.967369</td>\n",
              "      <td>-2.788697</td>\n",
              "      <td>-29.701198</td>\n",
              "      <td>-2.176432</td>\n",
              "      <td>10.025082</td>\n",
              "      <td>-1.435609</td>\n",
              "      <td>False</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>False</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  locus tag                f_primer_name                r_primer_name  \\\n",
              "0   SCO5087  SCO5087_fwd_checking_primer  SCO5087_rev_checking_primer   \n",
              "1   SCO5089  SCO5089_fwd_checking_primer  SCO5089_rev_checking_primer   \n",
              "2   SCO5090  SCO5090_fwd_checking_primer  SCO5090_rev_checking_primer   \n",
              "\n",
              "  f_primer_sequences(5-3) r_primer_sequences(5-3) f_tm r_tm  ta  \\\n",
              "0             TAGGGCGCGGC          CCGGAGACCACCAG   51   53  55   \n",
              "1          CCCTTCGACGAGCG              CGGGGCCGGT   54   49  53   \n",
              "2           CGAGCTGGACGCC          CGACGACCACCTCG   54   54  58   \n",
              "\n",
              "  flanking_region  annealing_temperature  \\\n",
              "0             550                     55   \n",
              "1             600                     53   \n",
              "2             600                     58   \n",
              "\n",
              "                                         primer_pair  homodimer_forward_tm  \\\n",
              "0  SCO5087_fwd_checking_primer & SCO5087_rev_chec...             26.385240   \n",
              "1  SCO5089_fwd_checking_primer & SCO5089_rev_chec...             -5.338917   \n",
              "2  SCO5090_fwd_checking_primer & SCO5090_rev_chec...            -27.967369   \n",
              "\n",
              "   homodimer_forward_deltaG (kcal/mol)  homodimer_reverse_tm  \\\n",
              "0                            -5.886397            -15.268430   \n",
              "1                            -1.468854              1.902964   \n",
              "2                            -2.788697            -29.701198   \n",
              "\n",
              "   homodimer_reverse_deltaG (kcal/mol)  heterodimer_tm  \\\n",
              "0                            -3.528618      -34.382170   \n",
              "1                            -3.360252      -36.526236   \n",
              "2                            -2.176432       10.025082   \n",
              "\n",
              "   heterodimer_deltaG (kcal/mol)  hairpin_forward_structure_found  \\\n",
              "0                      -1.534614                            False   \n",
              "1                      -1.541041                            False   \n",
              "2                      -1.435609                            False   \n",
              "\n",
              "   hairpin_forward_tm  hairpin_forward_deltaG (kcal/mol)  \\\n",
              "0                 0.0                                0.0   \n",
              "1                 0.0                                0.0   \n",
              "2                 0.0                                0.0   \n",
              "\n",
              "   hairpin_reverse_structure_found  hairpin_reverse_tm  \\\n",
              "0                            False                 0.0   \n",
              "1                            False                 0.0   \n",
              "2                            False                 0.0   \n",
              "\n",
              "   hairpin_reverse_deltaG (kcal/mol)  \n",
              "0                                0.0  \n",
              "1                                0.0  \n",
              "2                                0.0  "
            ]
          },
          "execution_count": 29,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "\n",
        "# Getting checking primers\n",
        "checking_primers_df = find_best_check_primers_from_genome(genome, \n",
        "                                       genes_to_KO, \n",
        "                                       flanking_region=flanking_region,\n",
        "                                       target_tm = melting_temperature, \n",
        "                                        primer_concentration = primer_concentration, \n",
        "                                        polymerase = chosen_polymerase)\n",
        "checking_primers_df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
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              "\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Name</th>\n",
              "      <th>Sequence</th>\n",
              "      <th>Concentration</th>\n",
              "      <th>Purification</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>SCO5087_fwd_checking_primer</td>\n",
              "      <td>TAGGGCGCGGC</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>SCO5089_fwd_checking_primer</td>\n",
              "      <td>CCCTTCGACGAGCG</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>SCO5090_fwd_checking_primer</td>\n",
              "      <td>CGAGCTGGACGCC</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>SCO5087_rev_checking_primer</td>\n",
              "      <td>CCGGAGACCACCAG</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>SCO5089_rev_checking_primer</td>\n",
              "      <td>CGGGGCCGGT</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>SCO5090_rev_checking_primer</td>\n",
              "      <td>CGACGACCACCTCG</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                          Name        Sequence Concentration Purification\n",
              "0  SCO5087_fwd_checking_primer     TAGGGCGCGGC          25nm          STD\n",
              "1  SCO5089_fwd_checking_primer  CCCTTCGACGAGCG          25nm          STD\n",
              "2  SCO5090_fwd_checking_primer   CGAGCTGGACGCC          25nm          STD\n",
              "3  SCO5087_rev_checking_primer  CCGGAGACCACCAG          25nm          STD\n",
              "4  SCO5089_rev_checking_primer      CGGGGCCGGT          25nm          STD\n",
              "5  SCO5090_rev_checking_primer  CGACGACCACCTCG          25nm          STD"
            ]
          },
          "execution_count": 30,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# making the primers into dseqrecords\n",
        "checking_primers_df_idt = create_idt_order_dataframe(checking_primers_df)\n",
        "checking_primers_df_idt\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
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              "<style scoped>\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Name</th>\n",
              "      <th>Sequence</th>\n",
              "      <th>Concentration</th>\n",
              "      <th>Purification</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>fwd_primer_SCO5090_140</td>\n",
              "      <td>GATCGGGTCTCCCATGGTTCACTGCCGTATAGGCAGCTAAGAAACA...</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>fwd_primer_SCO5090_208</td>\n",
              "      <td>GATCGGGTCTCCGGGACGTCCAGGTCTTCACCGTTTTAGAGCTAGA...</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>fwd_primer_SCO5087_522</td>\n",
              "      <td>GATCGGGTCTCCGTCGACCTCCCAGTCACGGCGTTTTAGAGCTAGA...</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>rev_primer_SCO5090_140</td>\n",
              "      <td>GATCAGGTCTCGTCCCAAAAAAGCACCGACTCG</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>rev_primer_SCO5090_208</td>\n",
              "      <td>GATCAGGTCTCGCGACAAAAAAGCACCGACTCG</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>rev_primer_SCO5087_522</td>\n",
              "      <td>GATCAGGTCTCGCTAGAAAAAAGCACCGACTCG</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>SCO5087_fwd_checking_primer</td>\n",
              "      <td>TAGGGCGCGGC</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>SCO5089_fwd_checking_primer</td>\n",
              "      <td>CCCTTCGACGAGCG</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>SCO5090_fwd_checking_primer</td>\n",
              "      <td>CGAGCTGGACGCC</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>SCO5087_rev_checking_primer</td>\n",
              "      <td>CCGGAGACCACCAG</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>SCO5089_rev_checking_primer</td>\n",
              "      <td>CGGGGCCGGT</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>SCO5090_rev_checking_primer</td>\n",
              "      <td>CGACGACCACCTCG</td>\n",
              "      <td>25nm</td>\n",
              "      <td>STD</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                          Name  \\\n",
              "0       fwd_primer_SCO5090_140   \n",
              "1       fwd_primer_SCO5090_208   \n",
              "2       fwd_primer_SCO5087_522   \n",
              "3       rev_primer_SCO5090_140   \n",
              "4       rev_primer_SCO5090_208   \n",
              "5       rev_primer_SCO5087_522   \n",
              "0  SCO5087_fwd_checking_primer   \n",
              "1  SCO5089_fwd_checking_primer   \n",
              "2  SCO5090_fwd_checking_primer   \n",
              "3  SCO5087_rev_checking_primer   \n",
              "4  SCO5089_rev_checking_primer   \n",
              "5  SCO5090_rev_checking_primer   \n",
              "\n",
              "                                            Sequence Concentration  \\\n",
              "0  GATCGGGTCTCCCATGGTTCACTGCCGTATAGGCAGCTAAGAAACA...          25nm   \n",
              "1  GATCGGGTCTCCGGGACGTCCAGGTCTTCACCGTTTTAGAGCTAGA...          25nm   \n",
              "2  GATCGGGTCTCCGTCGACCTCCCAGTCACGGCGTTTTAGAGCTAGA...          25nm   \n",
              "3                  GATCAGGTCTCGTCCCAAAAAAGCACCGACTCG          25nm   \n",
              "4                  GATCAGGTCTCGCGACAAAAAAGCACCGACTCG          25nm   \n",
              "5                  GATCAGGTCTCGCTAGAAAAAAGCACCGACTCG          25nm   \n",
              "0                                        TAGGGCGCGGC          25nm   \n",
              "1                                     CCCTTCGACGAGCG          25nm   \n",
              "2                                      CGAGCTGGACGCC          25nm   \n",
              "3                                     CCGGAGACCACCAG          25nm   \n",
              "4                                         CGGGGCCGGT          25nm   \n",
              "5                                     CGACGACCACCTCG          25nm   \n",
              "\n",
              "  Purification  \n",
              "0          STD  \n",
              "1          STD  \n",
              "2          STD  \n",
              "3          STD  \n",
              "4          STD  \n",
              "5          STD  \n",
              "0          STD  \n",
              "1          STD  \n",
              "2          STD  \n",
              "3          STD  \n",
              "4          STD  \n",
              "5          STD  "
            ]
          },
          "execution_count": 31,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "full_idt = pd.concat([idt_df, checking_primers_df_idt])\n",
        "full_idt"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Folder with all the generated I/O"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 32,
      "metadata": {},
      "outputs": [],
      "source": [
        "get_data_folder = False"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 33,
      "metadata": {},
      "outputs": [],
      "source": [
        "if get_data_folder: \n",
        "    # Example: \n",
        "\n",
        "    input_files = [\n",
        "        {\"name\": \"input_genome.gb\", \"content\": genome},\n",
        "        {\"name\": \"input_plasmid.gb\", \"content\": clean_plasmid}\n",
        "    ]\n",
        "\n",
        "    output_files = [\n",
        "        {\"name\": \"mcBEST_w_sgRNAs.gb\", \"content\": rec_vec},\n",
        "        {\"name\": \"overhang_df.csv\", \"content\": overhangs},\n",
        "        {\"name\": \"pcr_df.csv\", \"content\": primer_df},\n",
        "        {\"name\": \"full_idt.csv\", \"content\": full_idt},\n",
        "        {\"name\": \"mutated_sgrna_df.csv\", \"content\": mutated_sgrna_df},\n",
        "        {\"name\": \"filtered_df.csv\", \"content\": filtered_df},\n",
        "        {\"name\": \"plasmid_metadata_df.csv\", \"content\": plasmid_metadata_df},\n",
        "    ]\n",
        "\n",
        "    input_values = {\n",
        "        \"genes_to_knockout\": ['SCO5087', 'SCO5089', 'SCO5090'],\n",
        "        \"filtering_metrics\": {\n",
        "            \"gc_upper\": gc_upper,\n",
        "            \"gc_lower\": gc_lower,\n",
        "            \"off_target_seed\": off_target_seed,\n",
        "            \"off_target_upper\": off_target_upper,\n",
        "            \"cas_type\": cas_type,\n",
        "            \"number_of_sgRNAs_per_group\": number_of_sgRNAs_per_group\n",
        "        },\n",
        "        \"polymerase_settings\": {\n",
        "            \"chosen_polymerase\": chosen_polymerase,\n",
        "            \"melting_temperature\": melting_temperature,\n",
        "            \"primer_concentration\": primer_concentration,\n",
        "            \"flanking_region\": flanking_region\n",
        "        }, # TODO might want to incorporate this to the app\n",
        "        \"overlapping_sequences\": {\n",
        "            \"restriction_overhang_f\": restriction_overhang_f,\n",
        "            \"restriction_overhang_r\": restriction_overhang_r,\n",
        "            \"backbone_overhang_f\": backbone_overhang_f,\n",
        "            \"backbone_overhang_r\": backbone_overhang_r,\n",
        "            \"cys4\": cys4,\n",
        "            \"sgRNA_handle_cys4_site\": str(sgRNA_handle_cys4_site[0].seq)\n",
        "        }\n",
        "    }\n",
        "\n",
        "\n",
        "    # Paths to Markdown files\n",
        "    markdown_file_paths = [\n",
        "        \"../../protocols/conjugation_protcol.md\",\n",
        "        \"../../protocols/multi_target_crispr_plasmid_protcol.md\"\n",
        "\n",
        "    ]\n",
        "\n",
        "    # Data and time\n",
        "    timestamp = datetime.utcnow().isoformat()\n",
        "    project_name=f\"CRISPR_mcBEST_workflow_{timestamp}\"\n",
        "\n",
        "\n",
        "    # Create project directory structure\n",
        "    project_directory = ProjectDirectory(\n",
        "        project_name=project_name,\n",
        "        input_files=input_files,\n",
        "        output_files=output_files,\n",
        "        input_values=input_values,\n",
        "        markdown_file_paths=markdown_file_paths\n",
        "    )\n",
        "\n",
        "\n",
        "    # DO You want to save the folder? \n",
        "    save_zip_folder = False \n",
        "\n",
        "    if save_zip_folder: \n",
        "        # Generate the project directory structure and get the zip content\n",
        "        zip_content = project_directory.create_directory_structure(create_directories=False)\n",
        "\n",
        "        # Save the zip file to disk (optional)\n",
        "        with open(\"project_structure.zip\", \"wb\") as f:\n",
        "            f.write(zip_content)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "constrain",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.11.9"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 2
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