notebooks/generate_gene_embeddings.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## working with ESM2 embeddings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m→\u001b[0m connected lamindb: jkobject/scprint2\n"
     ]
    }
   ],
   "source": [
    "from scprint.tokenizers import protein_embeddings_generator\n",
    "#from RNABERT import RNABERT\n",
    "\n",
    "from scdataloader.utils import load_genes\n",
    "import pandas as pd\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# human"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>uid</th>\n",
       "      <th>symbol</th>\n",
       "      <th>ncbi_gene_ids</th>\n",
       "      <th>biotype</th>\n",
       "      <th>synonyms</th>\n",
       "      <th>description</th>\n",
       "      <th>organism_id</th>\n",
       "      <th>mt</th>\n",
       "      <th>ribo</th>\n",
       "      <th>hb</th>\n",
       "      <th>organism</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ensembl_gene_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ENSG00000000003</th>\n",
       "      <td>1uTi9dROoaN5</td>\n",
       "      <td>TSPAN6</td>\n",
       "      <td>7105</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>TSPAN-6|T245|TM4SF6</td>\n",
       "      <td>tetraspanin 6</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>NCBITaxon:9606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSG00000000005</th>\n",
       "      <td>2FhduD7Z97Uv</td>\n",
       "      <td>TNMD</td>\n",
       "      <td>64102</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>TEM|MYODULIN|CHM1L|TENDIN|BRICD4</td>\n",
       "      <td>tenomodulin</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>NCBITaxon:9606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSG00000000419</th>\n",
       "      <td>4eC1wUNJAO2s</td>\n",
       "      <td>DPM1</td>\n",
       "      <td>8813</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>CDGIE|MPDS</td>\n",
       "      <td>dolichyl-phosphate mannosyltransferase subunit...</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>NCBITaxon:9606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSG00000000457</th>\n",
       "      <td>5Zug63FETk4p</td>\n",
       "      <td>SCYL3</td>\n",
       "      <td>57147</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>PACE1|PACE-1</td>\n",
       "      <td>SCY1 like pseudokinase 3</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>NCBITaxon:9606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSG00000000460</th>\n",
       "      <td>3wEqb6eOTZzC</td>\n",
       "      <td>FIRRM</td>\n",
       "      <td>55732</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>C1ORF112|FLJ10706|APOLO1|FLIP|MEICA1</td>\n",
       "      <td>FIGNL1 interacting regulator of recombination ...</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>NCBITaxon:9606</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",
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       "    <tr>\n",
       "      <th>ENSG00000293596</th>\n",
       "      <td>42lwxhgTHxaN</td>\n",
       "      <td>None</td>\n",
       "      <td>105372654</td>\n",
       "      <td>lncRNA</td>\n",
       "      <td></td>\n",
       "      <td>novel transcript</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>NCBITaxon:9606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSG00000293597</th>\n",
       "      <td>12nPu7ce9hLZ</td>\n",
       "      <td>LINC00970</td>\n",
       "      <td>101978719</td>\n",
       "      <td>lncRNA</td>\n",
       "      <td></td>\n",
       "      <td>long intergenic non-protein coding RNA 970</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>NCBITaxon:9606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSG00000293599</th>\n",
       "      <td>2DLKDsGV0zX9</td>\n",
       "      <td>None</td>\n",
       "      <td></td>\n",
       "      <td>lncRNA</td>\n",
       "      <td></td>\n",
       "      <td>novel transcript</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>NCBITaxon:9606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSG00000293600</th>\n",
       "      <td>7hbNrFh6GVRt</td>\n",
       "      <td>None</td>\n",
       "      <td>131768270</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td></td>\n",
       "      <td>novel protein</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>NCBITaxon:9606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSG00000293604</th>\n",
       "      <td>43PKjUN2TuRj</td>\n",
       "      <td>ORAI1</td>\n",
       "      <td>84876</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>TMEM142A|CRACM1|FLJ14466</td>\n",
       "      <td>ORAI calcium release-activated calcium modulat...</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>NCBITaxon:9606</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>70704 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          uid     symbol ncbi_gene_ids         biotype  \\\n",
       "ensembl_gene_id                                                          \n",
       "ENSG00000000003  1uTi9dROoaN5     TSPAN6          7105  protein_coding   \n",
       "ENSG00000000005  2FhduD7Z97Uv       TNMD         64102  protein_coding   \n",
       "ENSG00000000419  4eC1wUNJAO2s       DPM1          8813  protein_coding   \n",
       "ENSG00000000457  5Zug63FETk4p      SCYL3         57147  protein_coding   \n",
       "ENSG00000000460  3wEqb6eOTZzC      FIRRM         55732  protein_coding   \n",
       "...                       ...        ...           ...             ...   \n",
       "ENSG00000293596  42lwxhgTHxaN       None     105372654          lncRNA   \n",
       "ENSG00000293597  12nPu7ce9hLZ  LINC00970     101978719          lncRNA   \n",
       "ENSG00000293599  2DLKDsGV0zX9       None                        lncRNA   \n",
       "ENSG00000293600  7hbNrFh6GVRt       None     131768270  protein_coding   \n",
       "ENSG00000293604  43PKjUN2TuRj      ORAI1         84876  protein_coding   \n",
       "\n",
       "                                             synonyms  \\\n",
       "ensembl_gene_id                                         \n",
       "ENSG00000000003                   TSPAN-6|T245|TM4SF6   \n",
       "ENSG00000000005      TEM|MYODULIN|CHM1L|TENDIN|BRICD4   \n",
       "ENSG00000000419                            CDGIE|MPDS   \n",
       "ENSG00000000457                          PACE1|PACE-1   \n",
       "ENSG00000000460  C1ORF112|FLJ10706|APOLO1|FLIP|MEICA1   \n",
       "...                                               ...   \n",
       "ENSG00000293596                                         \n",
       "ENSG00000293597                                         \n",
       "ENSG00000293599                                         \n",
       "ENSG00000293600                                         \n",
       "ENSG00000293604              TMEM142A|CRACM1|FLJ14466   \n",
       "\n",
       "                                                       description  \\\n",
       "ensembl_gene_id                                                      \n",
       "ENSG00000000003                                     tetraspanin 6    \n",
       "ENSG00000000005                                       tenomodulin    \n",
       "ENSG00000000419  dolichyl-phosphate mannosyltransferase subunit...   \n",
       "ENSG00000000457                          SCY1 like pseudokinase 3    \n",
       "ENSG00000000460  FIGNL1 interacting regulator of recombination ...   \n",
       "...                                                            ...   \n",
       "ENSG00000293596                                   novel transcript   \n",
       "ENSG00000293597        long intergenic non-protein coding RNA 970    \n",
       "ENSG00000293599                                   novel transcript   \n",
       "ENSG00000293600                                      novel protein   \n",
       "ENSG00000293604  ORAI calcium release-activated calcium modulat...   \n",
       "\n",
       "                 organism_id     mt   ribo     hb        organism  \n",
       "ensembl_gene_id                                                    \n",
       "ENSG00000000003            4  False  False  False  NCBITaxon:9606  \n",
       "ENSG00000000005            4  False  False  False  NCBITaxon:9606  \n",
       "ENSG00000000419            4  False  False  False  NCBITaxon:9606  \n",
       "ENSG00000000457            4  False  False  False  NCBITaxon:9606  \n",
       "ENSG00000000460            4  False  False  False  NCBITaxon:9606  \n",
       "...                      ...    ...    ...    ...             ...  \n",
       "ENSG00000293596            4  False  False  False  NCBITaxon:9606  \n",
       "ENSG00000293597            4  False  False  False  NCBITaxon:9606  \n",
       "ENSG00000293599            4  False  False  False  NCBITaxon:9606  \n",
       "ENSG00000293600            4  False  False  False  NCBITaxon:9606  \n",
       "ENSG00000293604            4  False  False  False  NCBITaxon:9606  \n",
       "\n",
       "[70704 rows x 11 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hgenedf = load_genes(organisms=\"NCBITaxon:9606\")\n",
    "hgenedf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "gzip: /tmp/data/fasta/Homo_sapiens.GRCh38.pep.all.fa already exists;\tnot overwritten\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "18017  genes had duplicates\n",
      "dropped 112 weird sequences\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9d2ab898658542a1816f398d28c360ed",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Fetching 4 files:   0%|          | 0/4 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "10975it [07:12, 25.04it/s]"
     ]
    }
   ],
   "source": [
    "#rm -r \"/tmp/data/fasta/\"\n",
    "homo_emb, naming_df = protein_embeddings_generator(hgenedf, organism=\"homo_sapiens\", cache=False, embedder=\"esm3\", embedding_size=1152, fasta_path = \"/tmp/data/fasta/\",)\n",
    "homo_emb.to_parquet(\"homo_emb.parquet\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# mouse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "mgenedf = load_genes(organisms=\"NCBITaxon:10090\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ml4ig1/Documents code/scPRINT/scprint/loaders/embedder.py:39: ResourceWarning: unclosed file <_io.BufferedReader name=107>\n",
      "  utils.utils.run_command([\"gunzip\", fasta_path + fasta_file])\n",
      "ResourceWarning: Enable tracemalloc to get the object allocation traceback\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "15073  genes had duplicates\n",
      "dropped 97 weird sequences\n",
      "running protbert\n",
      "b'Transferred model to GPU'\n",
      "b'Read /tmp/data/fasta/subset.fa with 21607 sequences'\n",
      "b'Processing 1 of 2950 batches (117 sequences)'\n",
      "b'Processing 2 of 2950 batches (89 sequences)'\n",
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     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ml4ig1/Documents code/scPRINT/scprint/loaders/protein_embedder.py:54: ResourceWarning: unclosed file <_io.BufferedReader name=107>\n",
      "  run_command(cmd, shell=True)\n",
      "ResourceWarning: Enable tracemalloc to get the object allocation traceback\n",
      "/home/ml4ig1/Documents code/scPRINT/scprint/loaders/embedder.py:53: ResourceWarning: unclosed file <_io.BufferedReader name=107>\n",
      "  utils.utils.run_command([\"gzip\", fasta_path + fasta_file[:-3]])\n",
      "ResourceWarning: Enable tracemalloc to get the object allocation traceback\n"
     ]
    }
   ],
   "source": [
    "#rm -r \"/tmp/data/fasta/\"\n",
    "mus_emb, naming_df = protein_embeddings_generator(mgenedf, organism=\"mus_musculus\", cache=False, embedder=\"esm3\", embedding_size=1152, fasta_path = \"/tmp/data/fasta/\",)\n",
    "mus_emb.to_parquet(\"mouse_emb.parquet\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "gene_emb = pd.concat([mus_emb, homo_emb])\n",
    "gene_emb.to_parquet(\"../data/main/gene_embeddings.parquet\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# other"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m→\u001b[0m connected lamindb: jkobject/scprint2\n"
     ]
    }
   ],
   "source": [
    "import bionty as bt\n",
    "import lamindb as ln"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Organism</th>\n",
       "      <td>ensembl</td>\n",
       "      <td>vertebrates</td>\n",
       "      <td>release-112</td>\n",
       "      <td>https://ftp.ensembl.org/pub/release-112/specie...</td>\n",
       "      <td>0ec37e77f4bc2d0b0b47c6c62b9f122d</td>\n",
       "      <td>Ensembl</td>\n",
       "      <td>https://www.ensembl.org</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Organism</th>\n",
       "      <td>ensembl</td>\n",
       "      <td>vertebrates</td>\n",
       "      <td>release-111</td>\n",
       "      <td>https://ftp.ensembl.org/pub/release-111/specie...</td>\n",
       "      <td>2846df83899eaa61f8043db4c036e883</td>\n",
       "      <td>Ensembl</td>\n",
       "      <td>https://www.ensembl.org</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Organism</th>\n",
       "      <td>ensembl</td>\n",
       "      <td>vertebrates</td>\n",
       "      <td>release-110</td>\n",
       "      <td>https://ftp.ensembl.org/pub/release-110/specie...</td>\n",
       "      <td>f3faf95648d3a2b50fd3625456739706</td>\n",
       "      <td>Ensembl</td>\n",
       "      <td>https://www.ensembl.org</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Organism</th>\n",
       "      <td>ensembl</td>\n",
       "      <td>vertebrates</td>\n",
       "      <td>release-109</td>\n",
       "      <td>https://ftp.ensembl.org/pub/release-109/specie...</td>\n",
       "      <td>7595bb989f5fec07eaca5e2138f67bd4</td>\n",
       "      <td>Ensembl</td>\n",
       "      <td>https://www.ensembl.org</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Organism</th>\n",
       "      <td>ensembl</td>\n",
       "      <td>vertebrates</td>\n",
       "      <td>release-108</td>\n",
       "      <td>https://ftp.ensembl.org/pub/release-108/specie...</td>\n",
       "      <td>d97c1ee302e4072f5f5c7850eff0b642</td>\n",
       "      <td>Ensembl</td>\n",
       "      <td>https://www.ensembl.org</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Organism</th>\n",
       "      <td>ensembl</td>\n",
       "      <td>bacteria</td>\n",
       "      <td>release-57</td>\n",
       "      <td>https://ftp.ensemblgenomes.ebi.ac.uk/pub/bacte...</td>\n",
       "      <td>ee28510ed5586ea7ab4495717c96efc8</td>\n",
       "      <td>Ensembl</td>\n",
       "      <td>https://www.ensembl.org</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Organism</th>\n",
       "      <td>ensembl</td>\n",
       "      <td>fungi</td>\n",
       "      <td>release-57</td>\n",
       "      <td>http://ftp.ensemblgenomes.org/pub/fungi/releas...</td>\n",
       "      <td>dbcde58f4396ab8b2480f7fe9f83df8a</td>\n",
       "      <td>Ensembl</td>\n",
       "      <td>https://www.ensembl.org</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Organism</th>\n",
       "      <td>ensembl</td>\n",
       "      <td>metazoa</td>\n",
       "      <td>release-57</td>\n",
       "      <td>http://ftp.ensemblgenomes.org/pub/metazoa/rele...</td>\n",
       "      <td>424636a574fec078a61cbdddb05f9132</td>\n",
       "      <td>Ensembl</td>\n",
       "      <td>https://www.ensembl.org</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Organism</th>\n",
       "      <td>ensembl</td>\n",
       "      <td>plants</td>\n",
       "      <td>release-57</td>\n",
       "      <td>https://ftp.ensemblgenomes.ebi.ac.uk/pub/plant...</td>\n",
       "      <td>eadaa1f3e527e4c3940c90c7fa5c8bf4</td>\n",
       "      <td>Ensembl</td>\n",
       "      <td>https://www.ensembl.org</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Organism</th>\n",
       "      <td>ncbitaxon</td>\n",
       "      <td>all</td>\n",
       "      <td>2023-06-20</td>\n",
       "      <td>s3://bionty-assets/df_all__ncbitaxon__2023-06-...</td>\n",
       "      <td>00d97ba65627f1cd65636d2df22ea76c</td>\n",
       "      <td>NCBItaxon Ontology</td>\n",
       "      <td>https://github.com/obophenotype/ncbitaxon</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             source     organism      version  \\\n",
       "entity                                          \n",
       "Organism    ensembl  vertebrates  release-112   \n",
       "Organism    ensembl  vertebrates  release-111   \n",
       "Organism    ensembl  vertebrates  release-110   \n",
       "Organism    ensembl  vertebrates  release-109   \n",
       "Organism    ensembl  vertebrates  release-108   \n",
       "Organism    ensembl     bacteria   release-57   \n",
       "Organism    ensembl        fungi   release-57   \n",
       "Organism    ensembl      metazoa   release-57   \n",
       "Organism    ensembl       plants   release-57   \n",
       "Organism  ncbitaxon          all   2023-06-20   \n",
       "\n",
       "                                                        url  \\\n",
       "entity                                                        \n",
       "Organism  https://ftp.ensembl.org/pub/release-112/specie...   \n",
       "Organism  https://ftp.ensembl.org/pub/release-111/specie...   \n",
       "Organism  https://ftp.ensembl.org/pub/release-110/specie...   \n",
       "Organism  https://ftp.ensembl.org/pub/release-109/specie...   \n",
       "Organism  https://ftp.ensembl.org/pub/release-108/specie...   \n",
       "Organism  https://ftp.ensemblgenomes.ebi.ac.uk/pub/bacte...   \n",
       "Organism  http://ftp.ensemblgenomes.org/pub/fungi/releas...   \n",
       "Organism  http://ftp.ensemblgenomes.org/pub/metazoa/rele...   \n",
       "Organism  https://ftp.ensemblgenomes.ebi.ac.uk/pub/plant...   \n",
       "Organism  s3://bionty-assets/df_all__ncbitaxon__2023-06-...   \n",
       "\n",
       "                                       md5         source_name  \\\n",
       "entity                                                           \n",
       "Organism  0ec37e77f4bc2d0b0b47c6c62b9f122d             Ensembl   \n",
       "Organism  2846df83899eaa61f8043db4c036e883             Ensembl   \n",
       "Organism  f3faf95648d3a2b50fd3625456739706             Ensembl   \n",
       "Organism  7595bb989f5fec07eaca5e2138f67bd4             Ensembl   \n",
       "Organism  d97c1ee302e4072f5f5c7850eff0b642             Ensembl   \n",
       "Organism  ee28510ed5586ea7ab4495717c96efc8             Ensembl   \n",
       "Organism  dbcde58f4396ab8b2480f7fe9f83df8a             Ensembl   \n",
       "Organism  424636a574fec078a61cbdddb05f9132             Ensembl   \n",
       "Organism  eadaa1f3e527e4c3940c90c7fa5c8bf4             Ensembl   \n",
       "Organism  00d97ba65627f1cd65636d2df22ea76c  NCBItaxon Ontology   \n",
       "\n",
       "                                     source_website  \n",
       "entity                                               \n",
       "Organism                    https://www.ensembl.org  \n",
       "Organism                    https://www.ensembl.org  \n",
       "Organism                    https://www.ensembl.org  \n",
       "Organism                    https://www.ensembl.org  \n",
       "Organism                    https://www.ensembl.org  \n",
       "Organism                    https://www.ensembl.org  \n",
       "Organism                    https://www.ensembl.org  \n",
       "Organism                    https://www.ensembl.org  \n",
       "Organism                    https://www.ensembl.org  \n",
       "Organism  https://github.com/obophenotype/ncbitaxon  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bt.base.display_available_sources().loc['Organism']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['root', 'cellvibrio', 'ancylobacter aquaticus',\n",
       "       'herbaspirillum sp. ba12', 'microbacterium sp. 6.11-vpa',\n",
       "       'callipharixenos sp. dpm-2011', 'paraxenos', 'paraxenos sp. dpm-2011',\n",
       "       'blissoxenos', 'blissoxenos esakii',\n",
       "       ...\n",
       "       'subspecies', 'subtribe', 'superclass', 'superfamily', 'superkingdom',\n",
       "       'superorder', 'superphylum', 'taxonomic rank', 'tribe', 'varietas'],\n",
       "      dtype='object', name='name', length=2511800)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bt.Organism.public(\"all\").df().index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[93m!\u001b[0m \u001b[1;91mdid not create\u001b[0m Organism record for \u001b[1;93m1 non-validated\u001b[0m \u001b[3mname\u001b[0m: \u001b[1;93m'caenorhabditis_elegans'\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "bt.Organism.from_source(name=\"caenorhabditis_elegans\", source=source)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "source = bt.PublicSource.filter(\n",
    "        name=\"ensembl\", organism=\"all\"\n",
    "    ).last()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[93m!\u001b[0m \u001b[1;91mdid not create\u001b[0m Organism record for \u001b[1;93m1 non-validated\u001b[0m \u001b[3mname\u001b[0m: \u001b[1;93m'caenorhabditis elegans (nematode, n2)'\u001b[0m\n",
      "\u001b[93m!\u001b[0m \u001b[1;91mdid not create\u001b[0m Organism record for \u001b[1;93m1 non-validated\u001b[0m \u001b[3mname\u001b[0m: \u001b[1;93m'panamanian white-faced capuchin'\u001b[0m\n",
      "\u001b[93m!\u001b[0m \u001b[1;91mdid not create\u001b[0m Organism record for \u001b[1;93m1 non-validated\u001b[0m \u001b[3mname\u001b[0m: \u001b[1;93m'atlantic herring '\u001b[0m\n",
      "\u001b[93m!\u001b[0m ambiguous validation in Bionty for 1 record: 'common carp'\n",
      "\u001b[93m!\u001b[0m \u001b[1;91mdid not create\u001b[0m Organism record for \u001b[1;93m1 non-validated\u001b[0m \u001b[3mname\u001b[0m: \u001b[1;93m'drosophila melanogaster (fruit fly)'\u001b[0m\n",
      "\u001b[93m!\u001b[0m \u001b[1;91mdid not create\u001b[0m Organism record for \u001b[1;93m1 non-validated\u001b[0m \u001b[3mname\u001b[0m: \u001b[1;93m'atlantic cod - celtic sea'\u001b[0m\n",
      "\u001b[93m!\u001b[0m \u001b[1;91mdid not create\u001b[0m Organism record for \u001b[1;93m1 non-validated\u001b[0m \u001b[3mname\u001b[0m: \u001b[1;93m'three-spined sticklebacki - freshwater bot'\u001b[0m\n",
      "\u001b[93m!\u001b[0m \u001b[1;91mdid not create\u001b[0m Organism record for \u001b[1;93m1 non-validated\u001b[0m \u001b[3mname\u001b[0m: \u001b[1;93m'three-spined sticklebacki - marine bam'\u001b[0m\n",
      "\u001b[93m!\u001b[0m \u001b[1;91mdid not create\u001b[0m Organism record for \u001b[1;93m1 non-validated\u001b[0m \u001b[3mname\u001b[0m: \u001b[1;93m'three-spined sticklebacki - marine syl'\u001b[0m\n",
      "\u001b[93m!\u001b[0m \u001b[1;91mdid not create\u001b[0m Organism record for \u001b[1;93m1 non-validated\u001b[0m \u001b[3mname\u001b[0m: \u001b[1;93m'korean mudskipper'\u001b[0m\n",
      "\u001b[93m!\u001b[0m \u001b[1;91mdid not create\u001b[0m Organism record for \u001b[1;93m1 non-validated\u001b[0m \u001b[3mname\u001b[0m: \u001b[1;93m'rat - shrsp/bbbutx'\u001b[0m\n",
      "\u001b[93m!\u001b[0m \u001b[1;91mdid not create\u001b[0m Organism record for \u001b[1;93m1 non-validated\u001b[0m \u001b[3mname\u001b[0m: \u001b[1;93m'rat - shr/utx rgd_8142385'\u001b[0m\n",
      "\u001b[93m!\u001b[0m \u001b[1;91mdid not create\u001b[0m Organism record for \u001b[1;93m1 non-validated\u001b[0m \u001b[3mname\u001b[0m: \u001b[1;93m'rat - wky/bbb rgd_1581635'\u001b[0m\n",
      "\u001b[93m!\u001b[0m \u001b[1;91mdid not create\u001b[0m Organism record for \u001b[1;93m1 non-validated\u001b[0m \u001b[3mname\u001b[0m: \u001b[1;93m'atlantic salmon - north american atlantic salmon'\u001b[0m\n",
      "\u001b[93m!\u001b[0m \u001b[1;91mdid not create\u001b[0m Organism record for \u001b[1;93m1 non-validated\u001b[0m \u001b[3mname\u001b[0m: \u001b[1;93m'atlantic salmon - north american origin brian'\u001b[0m\n",
      "\u001b[93m!\u001b[0m \u001b[1;91mdid not create\u001b[0m Organism record for \u001b[1;93m1 non-validated\u001b[0m \u001b[3mname\u001b[0m: \u001b[1;93m'atlantic salmon - european origin alta'\u001b[0m\n",
      "\u001b[92m→\u001b[0m returning existing Organism record with same name: 'unknown'\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Organism(uid='5HWRj1OD', name='unknown', ontology_id='unknown', created_by_id=1, space_id=1, created_at=2024-11-25 10:54:58 UTC)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "records = []\n",
    "for organism_clade in [\"vertebrates\", \"plants\"]:\n",
    "    names = bt.Organism.public(organism=organism_clade).df().index\n",
    "    source = bt.PublicSource.filter(\n",
    "        name=\"ensembl\", organism=organism_clade\n",
    "    ).last()\n",
    "    records += [\n",
    "        bt.Organism.from_source(name=name, source=source) for name in names\n",
    "    ]\n",
    "nrecords = []\n",
    "prevrec = set()\n",
    "for rec in records:\n",
    "    if rec is None:\n",
    "        continue\n",
    "    if not isinstance(rec, bt.Organism):\n",
    "        rec = rec[0]\n",
    "    if rec.uid not in prevrec:\n",
    "        nrecords.append(rec)\n",
    "        prevrec.add(rec.uid)\n",
    "ln.save(nrecords)\n",
    "bt.Organism(name=\"unknown\", ontology_id=\"unknown\").save()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "names = {\n",
    "    \"arabidopsis_thaliana\": \"NCBITaxon:3702\",\n",
    "    \"bos_taurus\": \"NCBITaxon:9913\",\n",
    "    \"caenorhabditis_elegans\": \"NCBITaxon:6239\",\n",
    "    \"callithrix_jacchus\": \"NCBITaxon:9483\",\n",
    "    \"danio_rerio\": \"NCBITaxon:7955\",\n",
    "    \"drosophila_melanogaster\": \"NCBITaxon:7227\",\n",
    "    \"gallus_gallus\": \"NCBITaxon:9031\",\n",
    "    \"heterocephalus_glaber_male\": \"NCBITaxon:10181\",\n",
    "    \"macaca_mulatta\": \"NCBITaxon:9544\",\n",
    "    \"oryctolagus_cuniculus\": \"NCBITaxon:9986\",\n",
    "    \"oryza_sativa\": \"NCBITaxon:39947\",\n",
    "    \"ovis_aries\": \"NCBITaxon:9940\",\n",
    "    \"pan_troglodytes\": \"NCBITaxon:9598\",\n",
    "    \"sus_scrofa\": \"NCBITaxon:9823\",\n",
    "    \"zea_mays\": \"NCBITaxon:4577\"\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in names.keys():\n",
    "    if i in [\"homo_sapiens\", \"mus_musculus\"]:\n",
    "        continue\n",
    "    emb, naming_df = protein_embeddings_generator(organism=i, cache=False, embedding_size=1152)\n",
    "    emb.to_parquet(f\"{i.split('_')[0]}_emb.parquet\")\n",
    "    naming_df.to_parquet(f\"{i.split('_')[0]}_names.parquet\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Grouping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mv: cannot stat 'mouse_emb.parquet': No such file or directory\n"
     ]
    }
   ],
   "source": [
    "! mv homo_emb.parquet ../homo_emb.parquet\n",
    "! mv mouse_emb.parquet ../mouse_emb.parquet\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "files = ! ls ../*_names.parquet\n",
    "files = [pd.read_parquet(i) for i in files]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "for j,file in enumerate(files):\n",
    "    file = file[file.biotype == \"protein_coding\"]\n",
    "    file = file.drop_duplicates(subset=[\"name\"])\n",
    "    file = file.rename(columns={\"name\": \"ensembl_gene_id\", \"gene_symbol\": \"symbol\"})\n",
    "    file['organism'] = list(names.values())[j]\n",
    "    file = file.set_index(\"ensembl_gene_id\")\n",
    "    file.to_parquet(f\"../{list(names.keys())[j].split('_')[0]}_names.parquet\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "files = ! ls ../*_names.parquet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "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>biotype</th>\n",
       "      <th>ensembl_id</th>\n",
       "      <th>symbol</th>\n",
       "      <th>description</th>\n",
       "      <th>organism</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ensembl_gene_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AT5G16970</th>\n",
       "      <td>protein_coding</td>\n",
       "      <td>AT5G16970.1</td>\n",
       "      <td>AER</td>\n",
       "      <td>alkenal reductase [Source:NCBI gene (formerly ...</td>\n",
       "      <td>NCBITaxon:3702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AT4G32100</th>\n",
       "      <td>protein_coding</td>\n",
       "      <td>AT4G32100.1</td>\n",
       "      <td>AT4G32100</td>\n",
       "      <td>Beta-1,3-N-Acetylglucosaminyltransferase famil...</td>\n",
       "      <td>NCBITaxon:3702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AT2G43120</th>\n",
       "      <td>protein_coding</td>\n",
       "      <td>AT2G43120.2</td>\n",
       "      <td>AT2G43120</td>\n",
       "      <td>RmlC-like cupins superfamily protein [Source:N...</td>\n",
       "      <td>NCBITaxon:3702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AT1G30814</th>\n",
       "      <td>protein_coding</td>\n",
       "      <td>AT1G30814.1</td>\n",
       "      <td>AT1G30814</td>\n",
       "      <td>uncharacterized protein [Source:NCBI gene (for...</td>\n",
       "      <td>NCBITaxon:3702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AT3G18710</th>\n",
       "      <td>protein_coding</td>\n",
       "      <td>AT3G18710.1</td>\n",
       "      <td>PUB29</td>\n",
       "      <td>plant U-box 29 [Source:NCBI gene (formerly Ent...</td>\n",
       "      <td>NCBITaxon:3702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zm00001eb324130</th>\n",
       "      <td>protein_coding</td>\n",
       "      <td>Zm00001eb324130_P001</td>\n",
       "      <td>Zm00001eb324130</td>\n",
       "      <td>Zm00001e138564</td>\n",
       "      <td>NCBITaxon:4577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zm00001eb266420</th>\n",
       "      <td>protein_coding</td>\n",
       "      <td>Zm00001eb266420_P001</td>\n",
       "      <td>Zm00001eb266420</td>\n",
       "      <td>Zm00001e029605</td>\n",
       "      <td>NCBITaxon:4577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zm00001eb100900</th>\n",
       "      <td>protein_coding</td>\n",
       "      <td>Zm00001eb100900_P001</td>\n",
       "      <td>Zm00001eb100900</td>\n",
       "      <td>Zm00001e009957</td>\n",
       "      <td>NCBITaxon:4577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zm00001eb385760</th>\n",
       "      <td>protein_coding</td>\n",
       "      <td>Zm00001eb385760_P001</td>\n",
       "      <td>Zm00001eb385760</td>\n",
       "      <td>Zm00001e037345</td>\n",
       "      <td>NCBITaxon:4577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zm00001eb080470</th>\n",
       "      <td>protein_coding</td>\n",
       "      <td>Zm00001eb080470_P001</td>\n",
       "      <td>Zm00001eb080470</td>\n",
       "      <td>Zm00001e007881</td>\n",
       "      <td>NCBITaxon:4577</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>487790 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        biotype            ensembl_id           symbol  \\\n",
       "ensembl_gene_id                                                          \n",
       "AT5G16970        protein_coding           AT5G16970.1              AER   \n",
       "AT4G32100        protein_coding           AT4G32100.1        AT4G32100   \n",
       "AT2G43120        protein_coding           AT2G43120.2        AT2G43120   \n",
       "AT1G30814        protein_coding           AT1G30814.1        AT1G30814   \n",
       "AT3G18710        protein_coding           AT3G18710.1            PUB29   \n",
       "...                         ...                   ...              ...   \n",
       "Zm00001eb324130  protein_coding  Zm00001eb324130_P001  Zm00001eb324130   \n",
       "Zm00001eb266420  protein_coding  Zm00001eb266420_P001  Zm00001eb266420   \n",
       "Zm00001eb100900  protein_coding  Zm00001eb100900_P001  Zm00001eb100900   \n",
       "Zm00001eb385760  protein_coding  Zm00001eb385760_P001  Zm00001eb385760   \n",
       "Zm00001eb080470  protein_coding  Zm00001eb080470_P001  Zm00001eb080470   \n",
       "\n",
       "                                                       description  \\\n",
       "ensembl_gene_id                                                      \n",
       "AT5G16970        alkenal reductase [Source:NCBI gene (formerly ...   \n",
       "AT4G32100        Beta-1,3-N-Acetylglucosaminyltransferase famil...   \n",
       "AT2G43120        RmlC-like cupins superfamily protein [Source:N...   \n",
       "AT1G30814        uncharacterized protein [Source:NCBI gene (for...   \n",
       "AT3G18710        plant U-box 29 [Source:NCBI gene (formerly Ent...   \n",
       "...                                                            ...   \n",
       "Zm00001eb324130                                     Zm00001e138564   \n",
       "Zm00001eb266420                                     Zm00001e029605   \n",
       "Zm00001eb100900                                     Zm00001e009957   \n",
       "Zm00001eb385760                                     Zm00001e037345   \n",
       "Zm00001eb080470                                     Zm00001e007881   \n",
       "\n",
       "                       organism  \n",
       "ensembl_gene_id                  \n",
       "AT5G16970        NCBITaxon:3702  \n",
       "AT4G32100        NCBITaxon:3702  \n",
       "AT2G43120        NCBITaxon:3702  \n",
       "AT1G30814        NCBITaxon:3702  \n",
       "AT3G18710        NCBITaxon:3702  \n",
       "...                         ...  \n",
       "Zm00001eb324130  NCBITaxon:4577  \n",
       "Zm00001eb266420  NCBITaxon:4577  \n",
       "Zm00001eb100900  NCBITaxon:4577  \n",
       "Zm00001eb385760  NCBITaxon:4577  \n",
       "Zm00001eb080470  NCBITaxon:4577  \n",
       "\n",
       "[487790 rows x 5 columns]"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_parquet(files)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# generate gene location file "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scdataloader.utils import getBiomartTable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "downloading gene names from biomart\n",
      "['start_position', 'chromosome_name', 'ensembl_gene_id']\n"
     ]
    },
    {
     "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>start_position</th>\n",
       "      <th>chromosome_name</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ensembl_gene_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ENSG00000290825</th>\n",
       "      <td>11869</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSG00000223972</th>\n",
       "      <td>12010</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSG00000227232</th>\n",
       "      <td>14696</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSG00000278267</th>\n",
       "      <td>17369</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSG00000243485</th>\n",
       "      <td>29554</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSG00000292373</th>\n",
       "      <td>57184216</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSG00000292369</th>\n",
       "      <td>57190738</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSG00000292370</th>\n",
       "      <td>57201143</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSG00000292372</th>\n",
       "      <td>57207346</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSG00000292371</th>\n",
       "      <td>57212184</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>70611 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 start_position chromosome_name\n",
       "ensembl_gene_id                                \n",
       "ENSG00000290825           11869               1\n",
       "ENSG00000223972           12010               1\n",
       "ENSG00000227232           14696               1\n",
       "ENSG00000278267           17369               1\n",
       "ENSG00000243485           29554               1\n",
       "...                         ...             ...\n",
       "ENSG00000292373        57184216               Y\n",
       "ENSG00000292369        57190738               Y\n",
       "ENSG00000292370        57201143               Y\n",
       "ENSG00000292372        57207346               Y\n",
       "ENSG00000292371        57212184               Y\n",
       "\n",
       "[70611 rows x 2 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table = getBiomartTable(ensemble_server = \"http://jan2024.archive.ensembl.org/biomart\", database=\"hsapiens_gene_ensembl\", attributes=['start_position', 'chromosome_name', 'ensembl_gene_id'], bypass_attributes=True).set_index('ensembl_gene_id') #mmusculus_gene_ensembl, hsapiens_gene_ensembl\n",
    "table = table.loc[~table.index.duplicated(keep='first')]\n",
    "table = table.sort_values(by=['chromosome_name', 'start_position'])\n",
    "table\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scdataloader import utils"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = utils.load_genes()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "gene_position_tolerance = 10_000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "reduced the size to 0.6722574020195106\n"
     ]
    }
   ],
   "source": [
    "c = []\n",
    "i = 0\n",
    "prev_position = -100_000\n",
    "prev_chromosome = None\n",
    "for _, r in table.iterrows():\n",
    "    if (\n",
    "        r[\"chromosome_name\"] != prev_chromosome\n",
    "        or r[\"start_position\"] - prev_position > gene_position_tolerance\n",
    "    ):\n",
    "        i += 1\n",
    "    c.append(i)\n",
    "    prev_position = r[\"start_position\"]\n",
    "    prev_chromosome = r[\"chromosome_name\"]\n",
    "print(f\"reduced the size to {len(set(c))/len(table)}\")\n",
    "table[\"pos\"] = c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "downloading gene names from biomart\n",
      "['ensembl_gene_id', 'hgnc_symbol', 'gene_biotype', 'entrezgene_id', 'start_position', 'chromosome_name']\n"
     ]
    },
    {
     "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>hgnc_symbol</th>\n",
       "      <th>gene_biotype</th>\n",
       "      <th>entrezgene_id</th>\n",
       "      <th>start_position</th>\n",
       "      <th>chromosome_name</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ensembl_gene_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ENSMUSG00000102693</th>\n",
       "      <td>ENSMUSG00000102693</td>\n",
       "      <td>TEC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3143476</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSMUSG00000064842</th>\n",
       "      <td>ENSMUSG00000064842</td>\n",
       "      <td>snRNA</td>\n",
       "      <td>115487594.0</td>\n",
       "      <td>3172239</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSMUSG00000051951</th>\n",
       "      <td>ENSMUSG00000051951</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>497097.0</td>\n",
       "      <td>3276124</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSMUSG00000102851</th>\n",
       "      <td>ENSMUSG00000102851</td>\n",
       "      <td>processed_pseudogene</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3322980</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSMUSG00000103377</th>\n",
       "      <td>ENSMUSG00000103377</td>\n",
       "      <td>TEC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3435954</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSMUSG00000099399</th>\n",
       "      <td>ENSMUSG00000099399</td>\n",
       "      <td>lncRNA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90676615</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSMUSG00000095366</th>\n",
       "      <td>ENSMUSG00000095366</td>\n",
       "      <td>lncRNA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90763696</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSMUSG00000095134</th>\n",
       "      <td>ENSMUSG00000095134</td>\n",
       "      <td>unprocessed_pseudogene</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90764326</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSMUSG00000096768</th>\n",
       "      <td>ENSMUSG00000096768</td>\n",
       "      <td>lncRNA</td>\n",
       "      <td>170942.0</td>\n",
       "      <td>90796007</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENSMUSG00000099871</th>\n",
       "      <td>ENSMUSG00000099871</td>\n",
       "      <td>unprocessed_pseudogene</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90848682</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>56941 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           hgnc_symbol            gene_biotype  entrezgene_id  \\\n",
       "ensembl_gene_id                                                                 \n",
       "ENSMUSG00000102693  ENSMUSG00000102693                     TEC            NaN   \n",
       "ENSMUSG00000064842  ENSMUSG00000064842                   snRNA    115487594.0   \n",
       "ENSMUSG00000051951  ENSMUSG00000051951          protein_coding       497097.0   \n",
       "ENSMUSG00000102851  ENSMUSG00000102851    processed_pseudogene            NaN   \n",
       "ENSMUSG00000103377  ENSMUSG00000103377                     TEC            NaN   \n",
       "...                                ...                     ...            ...   \n",
       "ENSMUSG00000099399  ENSMUSG00000099399                  lncRNA            NaN   \n",
       "ENSMUSG00000095366  ENSMUSG00000095366                  lncRNA            NaN   \n",
       "ENSMUSG00000095134  ENSMUSG00000095134  unprocessed_pseudogene            NaN   \n",
       "ENSMUSG00000096768  ENSMUSG00000096768                  lncRNA       170942.0   \n",
       "ENSMUSG00000099871  ENSMUSG00000099871  unprocessed_pseudogene            NaN   \n",
       "\n",
       "                    start_position chromosome_name  \n",
       "ensembl_gene_id                                     \n",
       "ENSMUSG00000102693         3143476               1  \n",
       "ENSMUSG00000064842         3172239               1  \n",
       "ENSMUSG00000051951         3276124               1  \n",
       "ENSMUSG00000102851         3322980               1  \n",
       "ENSMUSG00000103377         3435954               1  \n",
       "...                            ...             ...  \n",
       "ENSMUSG00000099399        90676615               Y  \n",
       "ENSMUSG00000095366        90763696               Y  \n",
       "ENSMUSG00000095134        90764326               Y  \n",
       "ENSMUSG00000096768        90796007               Y  \n",
       "ENSMUSG00000099871        90848682               Y  \n",
       "\n",
       "[56941 rows x 5 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table2 = getBiomartTable(database=\"mmusculus_gene_ensembl\", attributes=['start_position', 'chromosome_name']).set_index('ensembl_gene_id') #mmusculus_gene_ensembl, hsapiens_gene_ensembl\n",
    "table2 = table2.loc[~table2.index.duplicated(keep='first')]\n",
    "table2 = table2.sort_values(by=['chromosome_name', 'start_position'])\n",
    "table2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "reduced the size to 0.7208162835215398\n",
      "\n"
     ]
    }
   ],
   "source": [
    "c = []\n",
    "i = 0\n",
    "prev_position = -100000\n",
    "prev_chromosome = None\n",
    "for _, r in table2.iterrows():\n",
    "    if (\n",
    "        r[\"chromosome_name\"] != prev_chromosome\n",
    "        or r[\"start_position\"] - prev_position > gene_position_tolerance\n",
    "    ):\n",
    "        i += 1\n",
    "    c.append(i)\n",
    "    prev_position = r[\"start_position\"]\n",
    "    prev_chromosome = r[\"chromosome_name\"]\n",
    "print(f\"reduced the size to {len(set(c))/len(table2)}\")\n",
    "table2[\"pos\"] = c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "💡 connected lamindb: jkobject/scprint\n"
     ]
    }
   ],
   "source": [
    "from scdataloader import utils"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import bionty as bt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<QuerySet []>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bt.PublicSource.filter(\n",
    "    entity=\"Phenotype\",# source_website=\"pato\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Phenotype(uid='3OV8JZsS', name='female', ontology_id='PATO:0000383', description='A Biological Sex Quality Inhering In An Individual Or A Population That Only Produces Gametes That Can Be Fertilised By Male Gametes.', created_by_id=1, source_id=39, updated_at='2023-11-22 10:22:36 UTC')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bt.Phenotype.from_source(ontology_id=\"PATO:0000383\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<QuerySet [DevelopmentalStage(uid='4yqONmUe', name='106-year-old human stage', ontology_id='HsapDv:0000234', description='Aged Stage That Refers To An Adult Who Is Over 106 And Under 107.', created_by_id=1, source_id=44, updated_at='2023-11-28 12:55:35 UTC'), DevelopmentalStage(uid='2nBP50mg', name='first decade human stage', ontology_id='HsapDv:0000235', description='Human Stage That Refers To An Individual Who Is Over 0 And Under 10 Years Old.', created_by_id=1, source_id=44, updated_at='2023-11-28 12:55:35 UTC'), DevelopmentalStage(uid='2lfFHRoz', name='second decade human stage', ontology_id='HsapDv:0000236', description='Human Stage That Refers To An Individual Who Is Over 10 And Under 20 Years Old.', created_by_id=1, source_id=44, updated_at='2023-11-28 12:55:35 UTC'), DevelopmentalStage(uid='116jSpCp', name='tenth decade human stage', ontology_id='HsapDv:0000244', description='Human Stage That Refers To An Individual Who Is Over 90 And Under 100 Years Old.', created_by_id=1, source_id=44, updated_at='2023-11-28 12:55:35 UTC'), DevelopmentalStage(uid='71UGWwZD', name='eleventh decade human stage', ontology_id='HsapDv:0000245', description='Human Stage That Refers To A Human Who Is Over 100 And Under 110 Years Old.', created_by_id=1, source_id=44, updated_at='2023-11-28 12:55:35 UTC'), DevelopmentalStage(uid='3NMtboSP', name='centenarian human stage', ontology_id='HsapDv:0000247', description='Aged Stage That Refers To An Adult Who Is Over 100.', created_by_id=1, source_id=44, updated_at='2023-11-28 12:55:35 UTC'), DevelopmentalStage(uid='4EQ5pZnH', name='107-year-old human stage', ontology_id='HsapDv:0000248', description='Aged Stage That Refers To An Adult Who Is Over 107 And Under 108.', created_by_id=1, source_id=44, updated_at='2023-11-28 12:55:35 UTC'), DevelopmentalStage(uid='64wTuOyU', name='108-year-old human stage', ontology_id='HsapDv:0000249', description='Aged Stage That Refers To An Adult Who Is Over 108 And Under 109.', created_by_id=1, source_id=44, updated_at='2023-11-28 12:55:35 UTC'), DevelopmentalStage(uid='2uWRGkaK', name='109-year-old human stage', ontology_id='HsapDv:0000250', description='Aged Stage That Refers To An Adult Who Is Over 109 And Under 110.', created_by_id=1, source_id=44, updated_at='2023-11-28 12:55:35 UTC'), DevelopmentalStage(uid='2EPkljIU', name='110-year-old human stage', ontology_id='HsapDv:0000251', description='Aged Stage That Refers To An Adult Who Is Over 110 And Under 111.', created_by_id=1, source_id=44, updated_at='2023-11-28 12:55:35 UTC'), DevelopmentalStage(uid='2JsDotoq', name='111-year-old human stage', ontology_id='HsapDv:0000252', description='Aged Stage That Refers To An Adult Who Is Over 111 And Under 112.', created_by_id=1, source_id=44, updated_at='2023-11-28 12:55:35 UTC'), DevelopmentalStage(uid='lmvJZQde', name='112-year-old human stage', ontology_id='HsapDv:0000253', description='Aged Stage That Refers To An Adult Who Is Over 112 And Under 113.', created_by_id=1, source_id=44, updated_at='2023-11-28 12:55:35 UTC'), DevelopmentalStage(uid='U0US2U4S', name='113-year-old human stage', ontology_id='HsapDv:0000254', description='Aged Stage That Refers To An Adult Who Is Over 113 And Under 114.', created_by_id=1, source_id=44, updated_at='2023-11-28 12:55:35 UTC'), DevelopmentalStage(uid='7Pj1RpjN', name='114-year-old human stage', ontology_id='HsapDv:0000255', description='Aged Stage That Refers To An Adult Who Is Over 114 And Under 115.', created_by_id=1, source_id=44, updated_at='2023-11-28 12:55:35 UTC'), DevelopmentalStage(uid='7H4lnZbT', name='7 weeks', ontology_id='MmusDv:0000051', description='Early Adult Stage That Refers To A Mouse Which Is Over 49 Days And Under 57 Days Old.', created_by_id=1, source_id=45, updated_at='2024-03-20 20:46:33 UTC'), DevelopmentalStage(uid='1gCwII0u', name='8 weeks', ontology_id='MmusDv:0000052', description='2 Month-Old Stage That Refers To A Mouse Which Is Over 56 Days And Under 64 Days Old.', created_by_id=1, source_id=45, updated_at='2024-03-20 20:46:33 UTC'), DevelopmentalStage(uid='2xqsethz', name='9 weeks', ontology_id='MmusDv:0000053', description='2 Month-Old Stage That Refers To A Mouse Which Is Over 63 Days And Under 71 Days Old.', created_by_id=1, source_id=45, updated_at='2024-03-20 20:46:33 UTC'), DevelopmentalStage(uid='2ssAbReB', name='14 weeks', ontology_id='MmusDv:0000058', description='3 Month-Old Stage That Refers To A Mouse Which Is Over 98 Days And Under 106 Days Old.', created_by_id=1, source_id=45, updated_at='2024-03-20 20:46:34 UTC'), DevelopmentalStage(uid='7ArrXSuy', name='13 weeks', ontology_id='MmusDv:0000057', description='3 Month-Old Stage That Refers To A Mouse Which Is Over 91 Days And Under 99 Days Old.', created_by_id=1, source_id=45, updated_at='2024-03-20 20:46:33 UTC'), DevelopmentalStage(uid='5lY565b6', name='11 weeks', ontology_id='MmusDv:0000055', description='2 Month-Old Stage That Refers To A Mouse Which Is Over 77 Days And Under 85 Days Old.', created_by_id=1, source_id=45, updated_at='2024-03-20 20:46:33 UTC'), '...(remaining elements truncated)...']>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bt.DevelopmentalStage.filter()[330:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "bt.DevelopmentalStage.from_source"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "module 'bionty' has no attribute 'public'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[18], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m bionty_source \u001b[38;5;241m=\u001b[39m \u001b[43mbt\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpublic\u001b[49m()\u001b[38;5;241m.\u001b[39mfilter(\n\u001b[1;32m      2\u001b[0m     entity\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDevelopmentalStage\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m      3\u001b[0m )\n",
      "\u001b[0;31mAttributeError\u001b[0m: module 'bionty' has no attribute 'public'"
     ]
    }
   ],
   "source": [
    "bionty_source = bt.public().filter(\n",
    "    entity=\"DevelopmentalStage\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "💡 returning existing Organism record with same name: 'unknown'\n"
     ]
    },
    {
     "ename": "FieldError",
     "evalue": "Cannot resolve keyword 'source' into field. Choices are: _previous_runs, artifacts, cell_lines, cell_markers, cell_types, created_at, created_by, created_by_id, currently_used, dataframe_artifact, dataframe_artifact_id, description, developmental_stages, diseases, entity, ethnicities, experimental_factors, genes, id, in_db, md5, name, organism, organisms, pathways, phenotypes, proteins, run, run_id, source_website, tissues, uid, updated_at, url, version",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mFieldError\u001b[0m                                Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[4], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mutils\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpopulate_my_ontology\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m      2\u001b[0m \u001b[43m    \u001b[49m\u001b[43morganisms\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mNCBITaxon:10090\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mNCBITaxon:9606\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      3\u001b[0m \u001b[43m    \u001b[49m\u001b[43msex\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mPATO:0000384\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mPATO:0000383\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      4\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcelltypes\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m      5\u001b[0m \u001b[43m    \u001b[49m\u001b[43methnicities\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m      6\u001b[0m \u001b[43m    \u001b[49m\u001b[43massays\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m      7\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtissues\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m      8\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdiseases\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m      9\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdev_stages\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m     10\u001b[0m \u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/Documents code/scDataLoader/scdataloader/utils.py:429\u001b[0m, in \u001b[0;36mpopulate_my_ontology\u001b[0;34m(organisms, sex, celltypes, ethnicities, assays, tissues, diseases, dev_stages)\u001b[0m\n\u001b[1;32m    427\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m sex \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    428\u001b[0m     names \u001b[38;5;241m=\u001b[39m bt\u001b[38;5;241m.\u001b[39mPhenotype\u001b[38;5;241m.\u001b[39mpublic()\u001b[38;5;241m.\u001b[39mdf()\u001b[38;5;241m.\u001b[39mindex \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m sex \u001b[38;5;28;01melse\u001b[39;00m sex\n\u001b[0;32m--> 429\u001b[0m     records \u001b[38;5;241m=\u001b[39m [\n\u001b[1;32m    430\u001b[0m         bt\u001b[38;5;241m.\u001b[39mPhenotype\u001b[38;5;241m.\u001b[39mfrom_source(\n\u001b[1;32m    431\u001b[0m             ontology_id\u001b[38;5;241m=\u001b[39mi,\n\u001b[1;32m    432\u001b[0m             public_source\u001b[38;5;241m=\u001b[39mbt\u001b[38;5;241m.\u001b[39mPublicSource\u001b[38;5;241m.\u001b[39mfilter(\n\u001b[1;32m    433\u001b[0m                 entity\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mPhenotype\u001b[39m\u001b[38;5;124m\"\u001b[39m, source\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpato\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    434\u001b[0m             )\u001b[38;5;241m.\u001b[39mone(),\n\u001b[1;32m    435\u001b[0m         )\n\u001b[1;32m    436\u001b[0m         \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m names\n\u001b[1;32m    437\u001b[0m     ]\n\u001b[1;32m    438\u001b[0m     ln\u001b[38;5;241m.\u001b[39msave(records)\n\u001b[1;32m    439\u001b[0m     bt\u001b[38;5;241m.\u001b[39mPhenotype(name\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124munknown\u001b[39m\u001b[38;5;124m\"\u001b[39m, ontology_id\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124munknown\u001b[39m\u001b[38;5;124m\"\u001b[39m)\u001b[38;5;241m.\u001b[39msave()\n",
      "File \u001b[0;32m~/Documents code/scDataLoader/scdataloader/utils.py:432\u001b[0m, in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m    427\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m sex \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    428\u001b[0m     names \u001b[38;5;241m=\u001b[39m bt\u001b[38;5;241m.\u001b[39mPhenotype\u001b[38;5;241m.\u001b[39mpublic()\u001b[38;5;241m.\u001b[39mdf()\u001b[38;5;241m.\u001b[39mindex \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m sex \u001b[38;5;28;01melse\u001b[39;00m sex\n\u001b[1;32m    429\u001b[0m     records \u001b[38;5;241m=\u001b[39m [\n\u001b[1;32m    430\u001b[0m         bt\u001b[38;5;241m.\u001b[39mPhenotype\u001b[38;5;241m.\u001b[39mfrom_source(\n\u001b[1;32m    431\u001b[0m             ontology_id\u001b[38;5;241m=\u001b[39mi,\n\u001b[0;32m--> 432\u001b[0m             public_source\u001b[38;5;241m=\u001b[39m\u001b[43mbt\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mPublicSource\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfilter\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    433\u001b[0m \u001b[43m                \u001b[49m\u001b[43mentity\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mPhenotype\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msource\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mpato\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\n\u001b[1;32m    434\u001b[0m \u001b[43m            \u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mone(),\n\u001b[1;32m    435\u001b[0m         )\n\u001b[1;32m    436\u001b[0m         \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m names\n\u001b[1;32m    437\u001b[0m     ]\n\u001b[1;32m    438\u001b[0m     ln\u001b[38;5;241m.\u001b[39msave(records)\n\u001b[1;32m    439\u001b[0m     bt\u001b[38;5;241m.\u001b[39mPhenotype(name\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124munknown\u001b[39m\u001b[38;5;124m\"\u001b[39m, ontology_id\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124munknown\u001b[39m\u001b[38;5;124m\"\u001b[39m)\u001b[38;5;241m.\u001b[39msave()\n",
      "File \u001b[0;32m~/miniconda3/envs/scprint/lib/python3.10/site-packages/lamindb/_record.py:121\u001b[0m, in \u001b[0;36mfilter\u001b[0;34m(cls, **expressions)\u001b[0m\n\u001b[1;32m    118\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"{}\"\"\"\u001b[39;00m  \u001b[38;5;66;03m# noqa: D415\u001b[39;00m\n\u001b[1;32m    119\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlamindb\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_filter\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;28mfilter\u001b[39m\n\u001b[0;32m--> 121\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mfilter\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mexpressions\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/scprint/lib/python3.10/site-packages/lamindb/_filter.py:34\u001b[0m, in \u001b[0;36mfilter\u001b[0;34m(Record, **expressions)\u001b[0m\n\u001b[1;32m     32\u001b[0m qs \u001b[38;5;241m=\u001b[39m QuerySet(model\u001b[38;5;241m=\u001b[39mRecord, using\u001b[38;5;241m=\u001b[39m_using_key)\n\u001b[1;32m     33\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(expressions) \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m---> 34\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mqs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfilter\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mexpressions\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     35\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m     36\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m qs\n",
      "File \u001b[0;32m~/miniconda3/envs/scprint/lib/python3.10/site-packages/django/db/models/query.py:1476\u001b[0m, in \u001b[0;36mQuerySet.filter\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1471\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m   1472\u001b[0m \u001b[38;5;124;03mReturn a new QuerySet instance with the args ANDed to the existing\u001b[39;00m\n\u001b[1;32m   1473\u001b[0m \u001b[38;5;124;03mset.\u001b[39;00m\n\u001b[1;32m   1474\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m   1475\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_not_support_combined_queries(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfilter\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m-> 1476\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_filter_or_exclude\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/scprint/lib/python3.10/site-packages/django/db/models/query.py:1494\u001b[0m, in \u001b[0;36mQuerySet._filter_or_exclude\u001b[0;34m(self, negate, args, kwargs)\u001b[0m\n\u001b[1;32m   1492\u001b[0m     clone\u001b[38;5;241m.\u001b[39m_deferred_filter \u001b[38;5;241m=\u001b[39m negate, args, kwargs\n\u001b[1;32m   1493\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1494\u001b[0m     \u001b[43mclone\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_filter_or_exclude_inplace\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnegate\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1495\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m clone\n",
      "File \u001b[0;32m~/miniconda3/envs/scprint/lib/python3.10/site-packages/django/db/models/query.py:1501\u001b[0m, in \u001b[0;36mQuerySet._filter_or_exclude_inplace\u001b[0;34m(self, negate, args, kwargs)\u001b[0m\n\u001b[1;32m   1499\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_query\u001b[38;5;241m.\u001b[39madd_q(\u001b[38;5;241m~\u001b[39mQ(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs))\n\u001b[1;32m   1500\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1501\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_query\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43madd_q\u001b[49m\u001b[43m(\u001b[49m\u001b[43mQ\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/scprint/lib/python3.10/site-packages/django/db/models/sql/query.py:1613\u001b[0m, in \u001b[0;36mQuery.add_q\u001b[0;34m(self, q_object)\u001b[0m\n\u001b[1;32m   1604\u001b[0m \u001b[38;5;66;03m# For join promotion this case is doing an AND for the added q_object\u001b[39;00m\n\u001b[1;32m   1605\u001b[0m \u001b[38;5;66;03m# and existing conditions. So, any existing inner join forces the join\u001b[39;00m\n\u001b[1;32m   1606\u001b[0m \u001b[38;5;66;03m# type to remain inner. Existing outer joins can however be demoted.\u001b[39;00m\n\u001b[1;32m   1607\u001b[0m \u001b[38;5;66;03m# (Consider case where rel_a is LOUTER and rel_a__col=1 is added - if\u001b[39;00m\n\u001b[1;32m   1608\u001b[0m \u001b[38;5;66;03m# rel_a doesn't produce any rows, then the whole condition must fail.\u001b[39;00m\n\u001b[1;32m   1609\u001b[0m \u001b[38;5;66;03m# So, demotion is OK.\u001b[39;00m\n\u001b[1;32m   1610\u001b[0m existing_inner \u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m   1611\u001b[0m     a \u001b[38;5;28;01mfor\u001b[39;00m a \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39malias_map \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39malias_map[a]\u001b[38;5;241m.\u001b[39mjoin_type \u001b[38;5;241m==\u001b[39m INNER\n\u001b[1;32m   1612\u001b[0m }\n\u001b[0;32m-> 1613\u001b[0m clause, _ \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_add_q\u001b[49m\u001b[43m(\u001b[49m\u001b[43mq_object\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mused_aliases\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1614\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m clause:\n\u001b[1;32m   1615\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mwhere\u001b[38;5;241m.\u001b[39madd(clause, AND)\n",
      "File \u001b[0;32m~/miniconda3/envs/scprint/lib/python3.10/site-packages/django/db/models/sql/query.py:1645\u001b[0m, in \u001b[0;36mQuery._add_q\u001b[0;34m(self, q_object, used_aliases, branch_negated, current_negated, allow_joins, split_subq, check_filterable, summarize, update_join_types)\u001b[0m\n\u001b[1;32m   1641\u001b[0m joinpromoter \u001b[38;5;241m=\u001b[39m JoinPromoter(\n\u001b[1;32m   1642\u001b[0m     q_object\u001b[38;5;241m.\u001b[39mconnector, \u001b[38;5;28mlen\u001b[39m(q_object\u001b[38;5;241m.\u001b[39mchildren), current_negated\n\u001b[1;32m   1643\u001b[0m )\n\u001b[1;32m   1644\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m child \u001b[38;5;129;01min\u001b[39;00m q_object\u001b[38;5;241m.\u001b[39mchildren:\n\u001b[0;32m-> 1645\u001b[0m     child_clause, needed_inner \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbuild_filter\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1646\u001b[0m \u001b[43m        \u001b[49m\u001b[43mchild\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1647\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcan_reuse\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mused_aliases\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1648\u001b[0m \u001b[43m        \u001b[49m\u001b[43mbranch_negated\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbranch_negated\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1649\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcurrent_negated\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcurrent_negated\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1650\u001b[0m \u001b[43m        \u001b[49m\u001b[43mallow_joins\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mallow_joins\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1651\u001b[0m \u001b[43m        \u001b[49m\u001b[43msplit_subq\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msplit_subq\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1652\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcheck_filterable\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcheck_filterable\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1653\u001b[0m \u001b[43m        \u001b[49m\u001b[43msummarize\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msummarize\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1654\u001b[0m \u001b[43m        \u001b[49m\u001b[43mupdate_join_types\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mupdate_join_types\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1655\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1656\u001b[0m     joinpromoter\u001b[38;5;241m.\u001b[39madd_votes(needed_inner)\n\u001b[1;32m   1657\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m child_clause:\n",
      "File \u001b[0;32m~/miniconda3/envs/scprint/lib/python3.10/site-packages/django/db/models/sql/query.py:1495\u001b[0m, in \u001b[0;36mQuery.build_filter\u001b[0;34m(self, filter_expr, branch_negated, current_negated, can_reuse, allow_joins, split_subq, check_filterable, summarize, update_join_types)\u001b[0m\n\u001b[1;32m   1493\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m arg:\n\u001b[1;32m   1494\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m FieldError(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCannot parse keyword query \u001b[39m\u001b[38;5;132;01m%r\u001b[39;00m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m%\u001b[39m arg)\n\u001b[0;32m-> 1495\u001b[0m lookups, parts, reffed_expression \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msolve_lookup_type\u001b[49m\u001b[43m(\u001b[49m\u001b[43marg\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msummarize\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1497\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m check_filterable:\n\u001b[1;32m   1498\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcheck_filterable(reffed_expression)\n",
      "File \u001b[0;32m~/miniconda3/envs/scprint/lib/python3.10/site-packages/django/db/models/sql/query.py:1307\u001b[0m, in \u001b[0;36mQuery.solve_lookup_type\u001b[0;34m(self, lookup, summarize)\u001b[0m\n\u001b[1;32m   1305\u001b[0m             expression \u001b[38;5;241m=\u001b[39m Ref(annotation, expression)\n\u001b[1;32m   1306\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m expression_lookups, (), expression\n\u001b[0;32m-> 1307\u001b[0m _, field, _, lookup_parts \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mnames_to_path\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlookup_splitted\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_meta\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1308\u001b[0m field_parts \u001b[38;5;241m=\u001b[39m lookup_splitted[\u001b[38;5;241m0\u001b[39m : \u001b[38;5;28mlen\u001b[39m(lookup_splitted) \u001b[38;5;241m-\u001b[39m \u001b[38;5;28mlen\u001b[39m(lookup_parts)]\n\u001b[1;32m   1309\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(lookup_parts) \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m1\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m field_parts:\n",
      "File \u001b[0;32m~/miniconda3/envs/scprint/lib/python3.10/site-packages/django/db/models/sql/query.py:1772\u001b[0m, in \u001b[0;36mQuery.names_to_path\u001b[0;34m(self, names, opts, allow_many, fail_on_missing)\u001b[0m\n\u001b[1;32m   1764\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m pos \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m \u001b[38;5;129;01mor\u001b[39;00m fail_on_missing:\n\u001b[1;32m   1765\u001b[0m         available \u001b[38;5;241m=\u001b[39m \u001b[38;5;28msorted\u001b[39m(\n\u001b[1;32m   1766\u001b[0m             [\n\u001b[1;32m   1767\u001b[0m                 \u001b[38;5;241m*\u001b[39mget_field_names_from_opts(opts),\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   1770\u001b[0m             ]\n\u001b[1;32m   1771\u001b[0m         )\n\u001b[0;32m-> 1772\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m FieldError(\n\u001b[1;32m   1773\u001b[0m             \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCannot resolve keyword \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m into field. \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   1774\u001b[0m             \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mChoices are: \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m%\u001b[39m (name, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m, \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(available))\n\u001b[1;32m   1775\u001b[0m         )\n\u001b[1;32m   1776\u001b[0m     \u001b[38;5;28;01mbreak\u001b[39;00m\n\u001b[1;32m   1777\u001b[0m \u001b[38;5;66;03m# Check if we need any joins for concrete inheritance cases (the\u001b[39;00m\n\u001b[1;32m   1778\u001b[0m \u001b[38;5;66;03m# field lives in parent, but we are currently in one of its\u001b[39;00m\n\u001b[1;32m   1779\u001b[0m \u001b[38;5;66;03m# children)\u001b[39;00m\n",
      "\u001b[0;31mFieldError\u001b[0m: Cannot resolve keyword 'source' into field. Choices are: _previous_runs, artifacts, cell_lines, cell_markers, cell_types, created_at, created_by, created_by_id, currently_used, dataframe_artifact, dataframe_artifact_id, description, developmental_stages, diseases, entity, ethnicities, experimental_factors, genes, id, in_db, md5, name, organism, organisms, pathways, phenotypes, proteins, run, run_id, source_website, tissues, uid, updated_at, url, version"
     ]
    }
   ],
   "source": [
    "utils.populate_my_ontology(\n",
    "    organisms=[\"NCBITaxon:10090\", \"NCBITaxon:9606\"],\n",
    "    sex=[\"PATO:0000384\", \"PATO:0000383\"],\n",
    "    celltypes=None,\n",
    "    ethnicities=None,\n",
    "    assays=None,\n",
    "    tissues=None,\n",
    "    diseases=None,\n",
    "    dev_stages=None,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = pd.read_parquet(\"../data/main/biomart_pos.parquet\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "l = ['ENSG00000112096', 'ENSG00000137808', 'ENSG00000161149', 'ENSG00000182230', 'ENSG00000203812', 'ENSG00000204092', 'ENSG00000205485', 'ENSG00000212951', 'ENSG00000215271', 'ENSG00000221995', 'ENSG00000224739', 'ENSG00000224745', 'ENSG00000225178', 'ENSG00000225932', 'ENSG00000226377', 'ENSG00000226380', 'ENSG00000226403', 'ENSG00000227021', 'ENSG00000227220', 'ENSG00000227902', 'ENSG00000228139', 'ENSG00000228206', 'ENSG00000228906', 'ENSG00000229352', 'ENSG00000231575', 'ENSG00000232196', 'ENSG00000232295', 'ENSG00000233776', 'ENSG00000236166', 'ENSG00000236673', 'ENSG00000236740', 'ENSG00000236886', 'ENSG00000236996', 'ENSG00000237133', 'ENSG00000237513', 'ENSG00000237548', 'ENSG00000237838', 'ENSG00000239446', 'ENSG00000239467', 'ENSG00000239665', 'ENSG00000244693', 'ENSG00000244952', 'ENSG00000249860', 'ENSG00000251044', 'ENSG00000253878', 'ENSG00000254561', 'ENSG00000254740', 'ENSG00000255633', 'ENSG00000255823', 'ENSG00000256045', 'ENSG00000256222', 'ENSG00000256374', 'ENSG00000256427', 'ENSG00000256618', 'ENSG00000256863', 'ENSG00000256892', 'ENSG00000258414', 'ENSG00000258808', 'ENSG00000258861', 'ENSG00000259444', 'ENSG00000259820', 'ENSG00000259834', 'ENSG00000259855', 'ENSG00000260461', 'ENSG00000261068', 'ENSG00000261438', 'ENSG00000261490', 'ENSG00000261534', 'ENSG00000261737', 'ENSG00000261773', 'ENSG00000261963', 'ENSG00000262668', 'ENSG00000263464', 'ENSG00000267637', 'ENSG00000268955', 'ENSG00000269028', 'ENSG00000269900', 'ENSG00000269933', 'ENSG00000269966', 'ENSG00000270188', 'ENSG00000270394', 'ENSG00000270672', 'ENSG00000271043', 'ENSG00000271409', 'ENSG00000271734', 'ENSG00000271870', 'ENSG00000272040', 'ENSG00000272196', 'ENSG00000272267', 'ENSG00000272354', 'ENSG00000272370', 'ENSG00000272551', 'ENSG00000272567', 'ENSG00000272880', 'ENSG00000272904', 'ENSG00000272934', 'ENSG00000273301', 'ENSG00000273370', 'ENSG00000273496', 'ENSG00000273576', 'ENSG00000273614', 'ENSG00000273837', 'ENSG00000273888', 'ENSG00000273923', 'ENSG00000276612', 'ENSG00000276814', 'ENSG00000277050', 'ENSG00000277077', 'ENSG00000277352', 'ENSG00000277666', 'ENSG00000277761', 'ENSG00000278198', 'ENSG00000278782', 'ENSG00000278927', 'ENSG00000278955', 'ENSG00000279226', 'ENSG00000279765', 'ENSG00000279769', 'ENSG00000279948', 'ENSG00000280058', 'ENSG00000280095', 'ENSG00000280250', 'ENSG00000280346', 'ENSG00000280374', 'ENSG00000280710', 'ENSG00000282080', 'ENSG00000282246', 'ENSG00000282965', 'ENSG00000283486', 'ENSG00000284299', 'ENSG00000284741', 'ENSG00000285106', 'ENSG00000285162', 'ENSG00000285476', 'ENSG00000285762', 'ENSG00000286065', 'ENSG00000286228', 'ENSG00000286601', 'ENSG00000286699', 'ENSG00000286949', 'ENSG00000286996', 'ENSG00000287116', 'ENSG00000287388', 'ENSG00000288541', 'ENSG00000288546', 'ENSG00000288630', 'ENSG00000288639', 'ENSMUSG00000069518', 'ENSMUSG00000073682', 'ENSMUSG00000075014', 'ENSMUSG00000075015', 'ENSMUSG00000078091', 'ENSMUSG00000094958', 'ENSMUSG00000095547', 'ENSMUSG00000095891', 'ENSMUSG00000096385', 'ENSMUSG00000096519', 'ENSMUSG00000096923', 'ENSMUSG00000097078']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = a.reindex(a.index.tolist() + l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "a.to_parquet(\"../data/main/biomart_pos.parquet\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.concat([table, table2]).to_parquet(\"../data/main/biomart_pos.parquet\")"
   ]
  }
 ],
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