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README.md

@@ -1,3 +1,63 @@
----
-license: mit
----
+---
+license: mit
+task_categories:
+- tabular-regression
+tags:
+- biology
+- genomics
+pretty_name: "Borzoi Intervals"
+size_categories:
+- 100K<n<1M
+---
+
+# borzoi-data
+
+## Dataset Summary
+This dataset contains the specific genomic intervals used for training, validating, and testing the Borzoi model, a deep learning architecture for predicting functional genomic tracks from DNA sequence. The intervals are provided for both human and mouse genomes. We modified the intervals provided in the original source by extending the input sequence to 524,288 bp to create the full interval that was supplied to the model.
+
+- **Publication:** [Avsec, Ž., et al. "Effective gene expression prediction from sequence by integrating long-range interactions." Nat Methods 18, 1196–1203 (2021).](https://www.nature.com/articles/s41592-021-01252-x)
+- **Original Source** https://github.com/calico/borzoi/tree/main/data
+- **Genome Builds:**
+  - Human: hg38
+  - Mouse: mm10
+
+
+## Repository Content
+The repository includes two tab-separated values (TSV) files and two Jupyter notebooks:
+1. `human_intervals.tsv`: 55,497 genomic regions (excluding header).
+2. `mouse_intervals.tsv`: 49,369 genomic regions (excluding header).
+3. `data_human.ipynb`: Code to create `human_intervals.tsv`.
+4. `data_mouse.ipynb`: Code to create `mouse_intervals.tsv`.
+
+
+## Dataset Structure
+
+### Data Fields
+Both files follow a standard genomic interval format:
+
+| Column | Type | Description |
+| :--- | :--- | :--- |
+| `chrom` | string | Chromosome identifier (e.g., `chr18`, `chr4`) |
+| `start` | int | Start coordinate of the interval |
+| `end` | int | End coordinate of the interval |
+| `fold` | string | Fold assignment (`fold0`-`fold7`) |
+| `split` | string | Data partition assignment (`train`, `test`, or `val`) |
+
+### Statistics
+| File | Number of Regions | Genome Build |
+| :--- | :--- | :--- |
+| `human_intervals.tsv` | 55,497 | hg38 |
+| `mouse_intervals.tsv` | 49,369 | mm10 |
+
+## Usage
+
+```python
+from huggingface_hub import hf_hub_download
+import pandas as pd
+
+file_path = hf_hub_download(repo_id="Genentech/borzoi-data", filename="human_intervals.tsv")
+df_human = pd.read_csv(file_path, sep='\t')
+
+file_path = hf_hub_download(repo_id="Genentech/borzoi-data", filename="mouse_intervals.tsv")
+df_mouse = pd.read_csv(file_path, sep='\t')
+```

data_human.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "9233af61-78a9-45b7-a1c8-e882a780bffe",
+   "metadata": {},
+   "source": [
+    "# Process and save Borzoi genomic intervals"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "759f57dc-ef72-46d4-8409-bd7963f72fbd",
+   "metadata": {},
+   "source": [
+    "## Set up wandb"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "63bd594d-3be6-482b-885a-bf273aca4733",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[34m\u001b[1mwandb\u001b[0m: Using wandb-core as the SDK backend.  Please refer to https://wandb.me/wandb-core for more information.\n",
+      "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mavantikalal\u001b[0m (\u001b[33mgrelu\u001b[0m) to \u001b[32mhttps://api.wandb.ai\u001b[0m. Use \u001b[1m`wandb login --relogin`\u001b[0m to force relogin\n"
+     ]
+    }
+   ],
+   "source": [
+    "import wandb\n",
+    "import pandas as pd\n",
+    "\n",
+    "wandb.login(host=\"https://api.wandb.ai\")\n",
+    "project_name='borzoi'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "01fd2d09-9580-4c78-a0b0-b57df4101eef",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "Tracking run with wandb version 0.19.7"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "Run data is saved locally in <code>/code/github/gReLU-applications/borzoi/wandb/run-20250306_054006-tuf1j2g4</code>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "Syncing run <strong><a href='https://wandb.ai/grelu/borzoi/runs/tuf1j2g4' target=\"_blank\">prep-intervals-human</a></strong> to <a href='https://wandb.ai/grelu/borzoi' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/developer-guide' target=\"_blank\">docs</a>)<br>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       " View project at <a href='https://wandb.ai/grelu/borzoi' target=\"_blank\">https://wandb.ai/grelu/borzoi</a>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       " View run at <a href='https://wandb.ai/grelu/borzoi/runs/tuf1j2g4' target=\"_blank\">https://wandb.ai/grelu/borzoi/runs/tuf1j2g4</a>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "run = wandb.init(entity='grelu', project=project_name, job_type='preprocessing', name='prep-intervals-human',\n",
+    "    settings=wandb.Settings(\n",
+    "        program_relpath='data_human.ipynb',\n",
+    "        program_abspath='/code/github/gReLU-applications/borzoi/data_human.ipynb'\n",
+    "    ))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c9a6badc-b835-4d38-b134-6661960be06f",
+   "metadata": {},
+   "source": [
+    "## Load intervals"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "f6c3dd12-4e0c-43f2-9daf-cd821c85e3ed",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "intervals_path = '/gstore/data/resbioai/grelu/borzoi-data/hg38/sequences.bed'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "8a7a5189-3123-4926-8e75-cece1371ad9f",
+   "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>chrom</th>\n",
+       "      <th>start</th>\n",
+       "      <th>end</th>\n",
+       "      <th>fold</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>chr4</td>\n",
+       "      <td>82524421</td>\n",
+       "      <td>82721029</td>\n",
+       "      <td>fold0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chr13</td>\n",
+       "      <td>18604798</td>\n",
+       "      <td>18801406</td>\n",
+       "      <td>fold0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chr2</td>\n",
+       "      <td>189923408</td>\n",
+       "      <td>190120016</td>\n",
+       "      <td>fold0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   chrom      start        end   fold\n",
+       "0   chr4   82524421   82721029  fold0\n",
+       "1  chr13   18604798   18801406  fold0\n",
+       "2   chr2  189923408  190120016  fold0"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "intervals = pd.read_table(intervals_path, header=None)\n",
+    "intervals.columns = ['chrom', 'start', 'end', 'fold']\n",
+    "intervals.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "74efa465-b003-4a81-af6b-8511990ba1f1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "split\n",
+       "train    41699\n",
+       "val       6910\n",
+       "test      6888\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "intervals['split'] = 'train'\n",
+    "intervals.loc[intervals.fold=='fold3', 'split'] = 'test'\n",
+    "intervals.loc[intervals.fold=='fold4', 'split'] = 'val'\n",
+    "intervals.split.value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2dd99b47-a673-4213-a556-8fadb6b6feca",
+   "metadata": {},
+   "source": [
+    "## Resize intervals"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "bff3f031-c936-422c-9413-b50eedafb5b5",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/opt/conda/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\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>chrom</th>\n",
+       "      <th>start</th>\n",
+       "      <th>end</th>\n",
+       "      <th>fold</th>\n",
+       "      <th>split</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>chr4</td>\n",
+       "      <td>82360581</td>\n",
+       "      <td>82884869</td>\n",
+       "      <td>fold0</td>\n",
+       "      <td>train</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chr13</td>\n",
+       "      <td>18440958</td>\n",
+       "      <td>18965246</td>\n",
+       "      <td>fold0</td>\n",
+       "      <td>train</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chr2</td>\n",
+       "      <td>189759568</td>\n",
+       "      <td>190283856</td>\n",
+       "      <td>fold0</td>\n",
+       "      <td>train</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>chr10</td>\n",
+       "      <td>59711903</td>\n",
+       "      <td>60236191</td>\n",
+       "      <td>fold0</td>\n",
+       "      <td>train</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chr1</td>\n",
+       "      <td>116945627</td>\n",
+       "      <td>117469915</td>\n",
+       "      <td>fold0</td>\n",
+       "      <td>train</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   chrom      start        end   fold  split\n",
+       "0   chr4   82360581   82884869  fold0  train\n",
+       "1  chr13   18440958   18965246  fold0  train\n",
+       "2   chr2  189759568  190283856  fold0  train\n",
+       "3  chr10   59711903   60236191  fold0  train\n",
+       "4   chr1  116945627  117469915  fold0  train"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from grelu.sequence.utils import resize\n",
+    "intervals = resize(intervals, 524288)\n",
+    "intervals.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e065a48d-5033-497d-81c4-d12a8dc33b29",
+   "metadata": {},
+   "source": [
+    "## Save"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "f419b288-dcd4-4076-842f-9211d33f449c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "intervals.to_csv(\"human_intervals.tsv\", index=False, sep=\"\\t\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "47205dbe-d0f6-4db2-8df2-ad82e2189b84",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Artifact human_intervals>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "artifact = wandb.Artifact('human_intervals', type='dataset')\n",
+    "artifact.add_file(local_path=\"human_intervals.tsv\", name=\"data.tsv\")\n",
+    "run.log_artifact(artifact)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "9d13ced8-8755-4f20-acfb-cb59c5a1c5c2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       " View run <strong style=\"color:#cdcd00\">prep-intervals-human</strong> at: <a href='https://wandb.ai/grelu/borzoi/runs/tuf1j2g4' target=\"_blank\">https://wandb.ai/grelu/borzoi/runs/tuf1j2g4</a><br> View project at: <a href='https://wandb.ai/grelu/borzoi' target=\"_blank\">https://wandb.ai/grelu/borzoi</a><br>Synced 6 W&B file(s), 0 media file(s), 2 artifact file(s) and 0 other file(s)"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "Find logs at: <code>./wandb/run-20250306_054006-tuf1j2g4/logs</code>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "run.finish()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c1c5c691-bfcf-4601-9c30-b14e2260be96",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": 5
+}

data_mouse.ipynb

@@ -0,0 +1,471 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "9233af61-78a9-45b7-a1c8-e882a780bffe",
+   "metadata": {},
+   "source": [
+    "# Process and save Borzoi genomic intervals"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "759f57dc-ef72-46d4-8409-bd7963f72fbd",
+   "metadata": {},
+   "source": [
+    "## Set up wandb"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "63bd594d-3be6-482b-885a-bf273aca4733",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[34m\u001b[1mwandb\u001b[0m: Using wandb-core as the SDK backend.  Please refer to https://wandb.me/wandb-core for more information.\n",
+      "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mavantikalal\u001b[0m (\u001b[33mgrelu\u001b[0m) to \u001b[32mhttps://api.wandb.ai\u001b[0m. Use \u001b[1m`wandb login --relogin`\u001b[0m to force relogin\n"
+     ]
+    }
+   ],
+   "source": [
+    "import wandb\n",
+    "import pandas as pd\n",
+    "\n",
+    "wandb.login(host=\"https://api.wandb.ai\")\n",
+    "project_name='borzoi'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "01fd2d09-9580-4c78-a0b0-b57df4101eef",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "Tracking run with wandb version 0.19.7"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "Run data is saved locally in <code>/code/github/gReLU-applications/borzoi/wandb/run-20250306_054113-laagd3z3</code>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "Syncing run <strong><a href='https://wandb.ai/grelu/borzoi/runs/laagd3z3' target=\"_blank\">prep-intervals-mouse</a></strong> to <a href='https://wandb.ai/grelu/borzoi' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/developer-guide' target=\"_blank\">docs</a>)<br>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       " View project at <a href='https://wandb.ai/grelu/borzoi' target=\"_blank\">https://wandb.ai/grelu/borzoi</a>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       " View run at <a href='https://wandb.ai/grelu/borzoi/runs/laagd3z3' target=\"_blank\">https://wandb.ai/grelu/borzoi/runs/laagd3z3</a>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "run = wandb.init(entity='grelu', project=project_name, job_type='preprocessing', name='prep-intervals-mouse',\n",
+    "    settings=wandb.Settings(\n",
+    "        program_relpath='data_mouse.ipynb',\n",
+    "        program_abspath='/code/github/gReLU-applications/borzoi/data_mouse.ipynb'\n",
+    "    ))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c9a6badc-b835-4d38-b134-6661960be06f",
+   "metadata": {},
+   "source": [
+    "## Load intervals"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "f6c3dd12-4e0c-43f2-9daf-cd821c85e3ed",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "intervals_path = '/gstore/data/resbioai/grelu/borzoi-data/mm10/sequences.bed'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "8a7a5189-3123-4926-8e75-cece1371ad9f",
+   "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>chrom</th>\n",
+       "      <th>start</th>\n",
+       "      <th>end</th>\n",
+       "      <th>fold</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>chr1</td>\n",
+       "      <td>46257174</td>\n",
+       "      <td>46453782</td>\n",
+       "      <td>fold0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chr2</td>\n",
+       "      <td>83512641</td>\n",
+       "      <td>83709249</td>\n",
+       "      <td>fold0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chr7</td>\n",
+       "      <td>16218353</td>\n",
+       "      <td>16414961</td>\n",
+       "      <td>fold0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  chrom     start       end   fold\n",
+       "0  chr1  46257174  46453782  fold0\n",
+       "1  chr2  83512641  83709249  fold0\n",
+       "2  chr7  16218353  16414961  fold0"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "intervals = pd.read_table(intervals_path, header=None)\n",
+    "intervals.columns = ['chrom', 'start', 'end', 'fold']\n",
+    "intervals.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "74efa465-b003-4a81-af6b-8511990ba1f1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "split\n",
+       "train    36950\n",
+       "val       6318\n",
+       "test      6101\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "intervals['split'] = 'train'\n",
+    "intervals.loc[intervals.fold=='fold3', 'split'] = 'test'\n",
+    "intervals.loc[intervals.fold=='fold4', 'split'] = 'val'\n",
+    "intervals.split.value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2dd99b47-a673-4213-a556-8fadb6b6feca",
+   "metadata": {},
+   "source": [
+    "## Resize intervals"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "bff3f031-c936-422c-9413-b50eedafb5b5",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/opt/conda/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\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>chrom</th>\n",
+       "      <th>start</th>\n",
+       "      <th>end</th>\n",
+       "      <th>fold</th>\n",
+       "      <th>split</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>chr1</td>\n",
+       "      <td>46093334</td>\n",
+       "      <td>46617622</td>\n",
+       "      <td>fold0</td>\n",
+       "      <td>train</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chr2</td>\n",
+       "      <td>83348801</td>\n",
+       "      <td>83873089</td>\n",
+       "      <td>fold0</td>\n",
+       "      <td>train</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chr7</td>\n",
+       "      <td>16054513</td>\n",
+       "      <td>16578801</td>\n",
+       "      <td>fold0</td>\n",
+       "      <td>train</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>chr3</td>\n",
+       "      <td>113560579</td>\n",
+       "      <td>114084867</td>\n",
+       "      <td>fold0</td>\n",
+       "      <td>train</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chr3</td>\n",
+       "      <td>107306300</td>\n",
+       "      <td>107830588</td>\n",
+       "      <td>fold0</td>\n",
+       "      <td>train</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  chrom      start        end   fold  split\n",
+       "0  chr1   46093334   46617622  fold0  train\n",
+       "1  chr2   83348801   83873089  fold0  train\n",
+       "2  chr7   16054513   16578801  fold0  train\n",
+       "3  chr3  113560579  114084867  fold0  train\n",
+       "4  chr3  107306300  107830588  fold0  train"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from grelu.sequence.utils import resize\n",
+    "intervals = resize(intervals, 524288)\n",
+    "intervals.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e065a48d-5033-497d-81c4-d12a8dc33b29",
+   "metadata": {},
+   "source": [
+    "## Save"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "f419b288-dcd4-4076-842f-9211d33f449c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "intervals.to_csv(\"mouse_intervals.tsv\", index=False, sep=\"\\t\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "47205dbe-d0f6-4db2-8df2-ad82e2189b84",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Artifact mouse_intervals>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "artifact = wandb.Artifact('mouse_intervals', type='dataset')\n",
+    "artifact.add_file(local_path=\"mouse_intervals.tsv\", name=\"data.tsv\")\n",
+    "run.log_artifact(artifact)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "9d13ced8-8755-4f20-acfb-cb59c5a1c5c2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       " View run <strong style=\"color:#cdcd00\">prep-intervals-mouse</strong> at: <a href='https://wandb.ai/grelu/borzoi/runs/laagd3z3' target=\"_blank\">https://wandb.ai/grelu/borzoi/runs/laagd3z3</a><br> View project at: <a href='https://wandb.ai/grelu/borzoi' target=\"_blank\">https://wandb.ai/grelu/borzoi</a><br>Synced 6 W&B file(s), 0 media file(s), 2 artifact file(s) and 0 other file(s)"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "Find logs at: <code>./wandb/run-20250306_054113-laagd3z3/logs</code>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "run.finish()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c1c5c691-bfcf-4601-9c30-b14e2260be96",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": 5
+}