Updating labels to regression.ipynb

{
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   "cell_type": "code",
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   "source": [
    "from crr_labels import fantom\n",
    "from tqdm.auto import tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
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       "  0%|          | 0/5 [00:00<?, ?it/s]"
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   "source": [
    "from epigenomic_dataset.utils import get_cell_lines\n",
    "\n",
    "window_sizes = [64, 128, 256, 512, 1024]\n",
    "\n",
    "for window_size, (enhancers_fantom_hg38, promoters_fantom_hg38) in zip(tqdm(window_sizes), fantom(\n",
    "    # We retrieve the labels for all the cell lines we are interested in,\n",
    "    # whose epigenomic datasets are already made available from the `epigenomic_dataset`\n",
    "    # package.\n",
    "    # Since in FANTOM5 the cell line MCF-7 is encoded as MCF7, we need to\n",
    "    # remove the hyphen from the cell lines names.\n",
    "    cell_lines=[\n",
    "        cell_line.replace(\"-\", \"\")\n",
    "        for cell_line in get_cell_lines()\n",
    "    ],\n",
    "    # We will expand the sequence snippets to a size of 512\n",
    "    window_sizes=window_sizes,\n",
    "    # The genome version we want to use\n",
    "    genome=\"hg38\",\n",
    "    # We will not, for now, binarize the tasks\n",
    "    binarize=False,\n",
    ")):\n",
    "    path = f\"preprocessed/fantom/hg38/{window_size}/{{region}}.bed.xz\"\n",
    "    enhancers_fantom_hg38.to_csv(path.format(region=\"enhancers\"), sep=\"\\t\", index=False)\n",
    "    promoters_fantom_hg38.to_csv(path.format(region=\"promoters\"), sep=\"\\t\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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