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    "# Cell-Cycle Scoring and Regression\n",
    "\n",
    "This is a _Scanpy_ demo that shows how to regress cell cycle effect, following the approach showed in [Seurat's vignette](http://satijalab.org/seurat/cell_cycle_vignette.html#assign-cell-cycle-scores).\n",
    "As for the R example, toy dataset consists of murine hematopoietic progenitors from [Nestorowa et al., Blood 2016](https://doi.org/10.1182/blood-2016-05-716480).\n",
    "The files of the Seurat tutorial – used here for reasons of benchmarking – can be downloaded [here](https://www.dropbox.com/s/3dby3bjsaf5arrw/cell_cycle_vignette_files.zip?dl=1).\n",
    "A more recent version of the dataset can be downloaded [here](http://blood.stemcells.cam.ac.uk/data/nestorowa_corrected_log2_transformed_counts.txt.gz)."
   ]
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      "/home/phil/.local/share/hatch/env/virtual/scanpy-tutorials/vsyQHp6L/notebook/lib/python3.13/site-packages/session_info2/__init__.py:129: UserWarning: The '__version__' attribute is deprecated and will be removed in MarkupSafe 3.1. Use feature detection, or `importlib.metadata.version(\"markupsafe\")`, instead.\n",
      "  and (v := getattr(pkg, \"__version__\", None))\n"
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       "<table class=table>\n",
       "            <thead style=\"position: sticky; top: 0; background-color: var(--jp-layout-color0, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\">\n",
       "        <tr><th>Package</th><th>Version</th></tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td><strong>pooch</strong></td><td>1.8.2 (v1.8.2)</td></tr>\n",
       "        <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td><strong>scanpy</strong></td><td>1.11.4</td></tr>\n",
       "    </tbody>\n",
       "    <thead style=\"position: sticky; top: 0; background-color: var(--jp-layout-color0, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\">\n",
       "        <tr><th>Component</th><th>Info</th></tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>Python</td><td>3.13.7 (main, Aug 15 2025, 12:34:02) [GCC 15.2.1 20250813]</td></tr>\n",
       "        <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>OS</td><td>Linux-6.16.8-zen1-1-zen-x86_64-with-glibc2.42</td></tr>\n",
       "        <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>CPU</td><td>16 logical CPU cores</td></tr>\n",
       "        <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>GPU</td><td>No GPU found</td></tr>\n",
       "        <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>Updated</td><td>2025-09-22 08:42</td></tr>\n",
       "    </tbody>\n",
       "        </table>\n",
       "\n",
       "        <details>\n",
       "        <summary>Dependencies</summary>\n",
       "                <div style=\"max-height: min(500px, 80vh); overflow-y: auto;\">\n",
       "    <table class=table>\n",
       "            <thead style=\"position: sticky; top: 0; background-color: var(--jp-layout-color0, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\">\n",
       "    <tr><th>Dependency</th><th>Version</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>toolz</td><td>1.0.0</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>cloudpickle</td><td>3.1.1</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>Jinja2</td><td>3.1.6</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>sphinxcontrib-applehelp</td><td>2.0.0</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>pyparsing</td><td>3.2.5</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>debugpy</td><td>1.8.17</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>ipython</td><td>9.5.0</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>sphinxcontrib-htmlhelp</td><td>2.1.0</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>parso</td><td>0.8.5</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>legacy-api-wrap</td><td>1.4.1</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>decorator</td><td>5.2.1</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>Pygments</td><td>2.19.2</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>matplotlib</td><td>3.10.6</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>cycler</td><td>0.12.1</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>pytz</td><td>2025.2</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>numpy</td><td>2.3.3</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>platformdirs</td><td>4.4.0</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>comm</td><td>0.2.3</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>jedi</td><td>0.19.2</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>PyYAML</td><td>6.0.2</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>python-dateutil</td><td>2.9.0.post0</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>sphinxcontrib-jsmath</td><td>1.0.1</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>six</td><td>1.17.0</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>llvmlite</td><td>0.45.0</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>numba</td><td>0.62.0</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>threadpoolctl</td><td>3.6.0</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>joblib</td><td>1.5.2</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>scipy</td><td>1.16.2</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>ipykernel</td><td>6.30.1</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>dask</td><td>2025.9.1</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>stack-data</td><td>0.6.3</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>MarkupSafe</td><td>3.0.2</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>jupyter_core</td><td>5.8.1</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>natsort</td><td>8.4.0</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>texttable</td><td>1.7.0</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>h5py</td><td>3.14.0</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>pyzmq</td><td>27.1.0</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>tblib</td><td>3.1.0</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>sphinxcontrib-devhelp</td><td>2.0.0</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>pandas</td><td>2.3.2</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>traitlets</td><td>5.14.3</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>packaging</td><td>25.0</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>anndata</td><td>0.11.3</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>tornado</td><td>6.5.2</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>pure_eval</td><td>0.2.3</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>sphinxcontrib-serializinghtml</td><td>2.0.0</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>sphinxcontrib-qthelp</td><td>2.0.0</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>asttokens</td><td>3.0.0</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>kiwisolver</td><td>1.4.9</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>tqdm</td><td>4.67.1</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>executing</td><td>2.2.1</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>psutil</td><td>7.1.0</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>pillow</td><td>11.3.0</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>charset-normalizer</td><td>3.4.3</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>wcwidth</td><td>0.2.13</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>igraph</td><td>0.11.9</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>scikit-learn</td><td>1.7.2</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>session-info2</td><td>0.2.2</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>prompt_toolkit</td><td>3.0.52</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color2, var(--vscode-tree-tableOddRowsBackground, #f1f3f4)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>leidenalg</td><td>0.10.2</td></tr>\n",
       "    <tr style=\"background-color: var(--jp-layout-color1, var(--vscode-editor-background, #f8f9fa)); color: var(--jp-ui-font-color1, var(--vscode-editor-foreground, #212529));\"><td>jupyter_client</td><td>8.6.3</td></tr>\n",
       "</tbody>\n",
       "    </table>\n",
       "</div>\n",
       "    </details>\n",
       "        <details>\n",
       "            <summary>Copyable Markdown</summary>\n",
       "            <pre>| Package | Version        |\n",
       "| ------- | -------------- |\n",
       "| pooch   | 1.8.2 (v1.8.2) |\n",
       "| scanpy  | 1.11.4         |\n",
       "\n",
       "| Dependency                    | Version     |\n",
       "| ----------------------------- | ----------- |\n",
       "| toolz                         | 1.0.0       |\n",
       "| cloudpickle                   | 3.1.1       |\n",
       "| Jinja2                        | 3.1.6       |\n",
       "| sphinxcontrib-applehelp       | 2.0.0       |\n",
       "| pyparsing                     | 3.2.5       |\n",
       "| debugpy                       | 1.8.17      |\n",
       "| ipython                       | 9.5.0       |\n",
       "| sphinxcontrib-htmlhelp        | 2.1.0       |\n",
       "| parso                         | 0.8.5       |\n",
       "| legacy-api-wrap               | 1.4.1       |\n",
       "| decorator                     | 5.2.1       |\n",
       "| Pygments                      | 2.19.2      |\n",
       "| matplotlib                    | 3.10.6      |\n",
       "| cycler                        | 0.12.1      |\n",
       "| pytz                          | 2025.2      |\n",
       "| numpy                         | 2.3.3       |\n",
       "| platformdirs                  | 4.4.0       |\n",
       "| comm                          | 0.2.3       |\n",
       "| jedi                          | 0.19.2      |\n",
       "| PyYAML                        | 6.0.2       |\n",
       "| python-dateutil               | 2.9.0.post0 |\n",
       "| sphinxcontrib-jsmath          | 1.0.1       |\n",
       "| six                           | 1.17.0      |\n",
       "| llvmlite                      | 0.45.0      |\n",
       "| numba                         | 0.62.0      |\n",
       "| threadpoolctl                 | 3.6.0       |\n",
       "| joblib                        | 1.5.2       |\n",
       "| scipy                         | 1.16.2      |\n",
       "| ipykernel                     | 6.30.1      |\n",
       "| dask                          | 2025.9.1    |\n",
       "| stack-data                    | 0.6.3       |\n",
       "| MarkupSafe                    | 3.0.2       |\n",
       "| jupyter_core                  | 5.8.1       |\n",
       "| natsort                       | 8.4.0       |\n",
       "| texttable                     | 1.7.0       |\n",
       "| h5py                          | 3.14.0      |\n",
       "| pyzmq                         | 27.1.0      |\n",
       "| tblib                         | 3.1.0       |\n",
       "| sphinxcontrib-devhelp         | 2.0.0       |\n",
       "| pandas                        | 2.3.2       |\n",
       "| traitlets                     | 5.14.3      |\n",
       "| packaging                     | 25.0        |\n",
       "| anndata                       | 0.11.3      |\n",
       "| tornado                       | 6.5.2       |\n",
       "| pure_eval                     | 0.2.3       |\n",
       "| sphinxcontrib-serializinghtml | 2.0.0       |\n",
       "| sphinxcontrib-qthelp          | 2.0.0       |\n",
       "| asttokens                     | 3.0.0       |\n",
       "| kiwisolver                    | 1.4.9       |\n",
       "| tqdm                          | 4.67.1      |\n",
       "| executing                     | 2.2.1       |\n",
       "| psutil                        | 7.1.0       |\n",
       "| pillow                        | 11.3.0      |\n",
       "| charset-normalizer            | 3.4.3       |\n",
       "| wcwidth                       | 0.2.13      |\n",
       "| igraph                        | 0.11.9      |\n",
       "| scikit-learn                  | 1.7.2       |\n",
       "| session-info2                 | 0.2.2       |\n",
       "| prompt_toolkit                | 3.0.52      |\n",
       "| leidenalg                     | 0.10.2      |\n",
       "| jupyter_client                | 8.6.3       |\n",
       "\n",
       "| Component | Info                                                       |\n",
       "| --------- | ---------------------------------------------------------- |\n",
       "| Python    | 3.13.7 (main, Aug 15 2025, 12:34:02) [GCC 15.2.1 20250813] |\n",
       "| OS        | Linux-6.16.8-zen1-1-zen-x86_64-with-glibc2.42              |\n",
       "| CPU       | 16 logical CPU cores                                       |\n",
       "| GPU       | No GPU found                                               |\n",
       "| Updated   | 2025-09-22 08:42                                           |</pre>\n",
       "        </details>"
      ],
      "text/markdown": [
       "| Package | Version        |\n",
       "| ------- | -------------- |\n",
       "| pooch   | 1.8.2 (v1.8.2) |\n",
       "| scanpy  | 1.11.4         |\n",
       "\n",
       "| Dependency                    | Version     |\n",
       "| ----------------------------- | ----------- |\n",
       "| toolz                         | 1.0.0       |\n",
       "| cloudpickle                   | 3.1.1       |\n",
       "| Jinja2                        | 3.1.6       |\n",
       "| sphinxcontrib-applehelp       | 2.0.0       |\n",
       "| pyparsing                     | 3.2.5       |\n",
       "| debugpy                       | 1.8.17      |\n",
       "| ipython                       | 9.5.0       |\n",
       "| sphinxcontrib-htmlhelp        | 2.1.0       |\n",
       "| parso                         | 0.8.5       |\n",
       "| legacy-api-wrap               | 1.4.1       |\n",
       "| decorator                     | 5.2.1       |\n",
       "| Pygments                      | 2.19.2      |\n",
       "| matplotlib                    | 3.10.6      |\n",
       "| cycler                        | 0.12.1      |\n",
       "| pytz                          | 2025.2      |\n",
       "| numpy                         | 2.3.3       |\n",
       "| platformdirs                  | 4.4.0       |\n",
       "| comm                          | 0.2.3       |\n",
       "| jedi                          | 0.19.2      |\n",
       "| PyYAML                        | 6.0.2       |\n",
       "| python-dateutil               | 2.9.0.post0 |\n",
       "| sphinxcontrib-jsmath          | 1.0.1       |\n",
       "| six                           | 1.17.0      |\n",
       "| llvmlite                      | 0.45.0      |\n",
       "| numba                         | 0.62.0      |\n",
       "| threadpoolctl                 | 3.6.0       |\n",
       "| joblib                        | 1.5.2       |\n",
       "| scipy                         | 1.16.2      |\n",
       "| ipykernel                     | 6.30.1      |\n",
       "| dask                          | 2025.9.1    |\n",
       "| stack-data                    | 0.6.3       |\n",
       "| MarkupSafe                    | 3.0.2       |\n",
       "| jupyter_core                  | 5.8.1       |\n",
       "| natsort                       | 8.4.0       |\n",
       "| texttable                     | 1.7.0       |\n",
       "| h5py                          | 3.14.0      |\n",
       "| pyzmq                         | 27.1.0      |\n",
       "| tblib                         | 3.1.0       |\n",
       "| sphinxcontrib-devhelp         | 2.0.0       |\n",
       "| pandas                        | 2.3.2       |\n",
       "| traitlets                     | 5.14.3      |\n",
       "| packaging                     | 25.0        |\n",
       "| anndata                       | 0.11.3      |\n",
       "| tornado                       | 6.5.2       |\n",
       "| pure_eval                     | 0.2.3       |\n",
       "| sphinxcontrib-serializinghtml | 2.0.0       |\n",
       "| sphinxcontrib-qthelp          | 2.0.0       |\n",
       "| asttokens                     | 3.0.0       |\n",
       "| kiwisolver                    | 1.4.9       |\n",
       "| tqdm                          | 4.67.1      |\n",
       "| executing                     | 2.2.1       |\n",
       "| psutil                        | 7.1.0       |\n",
       "| pillow                        | 11.3.0      |\n",
       "| charset-normalizer            | 3.4.3       |\n",
       "| wcwidth                       | 0.2.13      |\n",
       "| igraph                        | 0.11.9      |\n",
       "| scikit-learn                  | 1.7.2       |\n",
       "| session-info2                 | 0.2.2       |\n",
       "| prompt_toolkit                | 3.0.52      |\n",
       "| leidenalg                     | 0.10.2      |\n",
       "| jupyter_client                | 8.6.3       |\n",
       "\n",
       "| Component | Info                                                       |\n",
       "| --------- | ---------------------------------------------------------- |\n",
       "| Python    | 3.13.7 (main, Aug 15 2025, 12:34:02) [GCC 15.2.1 20250813] |\n",
       "| OS        | Linux-6.16.8-zen1-1-zen-x86_64-with-glibc2.42              |\n",
       "| CPU       | 16 logical CPU cores                                       |\n",
       "| GPU       | No GPU found                                               |\n",
       "| Updated   | 2025-09-22 08:42                                           |"
      ],
      "text/plain": [
       "pooch\t1.8.2 (v1.8.2)\n",
       "scanpy\t1.11.4\n",
       "----\t----\n",
       "toolz\t1.0.0\n",
       "cloudpickle\t3.1.1\n",
       "Jinja2\t3.1.6\n",
       "sphinxcontrib-applehelp\t2.0.0\n",
       "pyparsing\t3.2.5\n",
       "debugpy\t1.8.17\n",
       "ipython\t9.5.0\n",
       "sphinxcontrib-htmlhelp\t2.1.0\n",
       "parso\t0.8.5\n",
       "legacy-api-wrap\t1.4.1\n",
       "decorator\t5.2.1\n",
       "Pygments\t2.19.2\n",
       "matplotlib\t3.10.6\n",
       "cycler\t0.12.1\n",
       "pytz\t2025.2\n",
       "numpy\t2.3.3\n",
       "platformdirs\t4.4.0\n",
       "comm\t0.2.3\n",
       "jedi\t0.19.2\n",
       "PyYAML\t6.0.2\n",
       "python-dateutil\t2.9.0.post0\n",
       "sphinxcontrib-jsmath\t1.0.1\n",
       "six\t1.17.0\n",
       "llvmlite\t0.45.0\n",
       "numba\t0.62.0\n",
       "threadpoolctl\t3.6.0\n",
       "joblib\t1.5.2\n",
       "scipy\t1.16.2\n",
       "ipykernel\t6.30.1\n",
       "dask\t2025.9.1\n",
       "stack-data\t0.6.3\n",
       "MarkupSafe\t3.0.2\n",
       "jupyter_core\t5.8.1\n",
       "natsort\t8.4.0\n",
       "texttable\t1.7.0\n",
       "h5py\t3.14.0\n",
       "pyzmq\t27.1.0\n",
       "tblib\t3.1.0\n",
       "sphinxcontrib-devhelp\t2.0.0\n",
       "pandas\t2.3.2\n",
       "traitlets\t5.14.3\n",
       "packaging\t25.0\n",
       "anndata\t0.11.3\n",
       "tornado\t6.5.2\n",
       "pure_eval\t0.2.3\n",
       "sphinxcontrib-serializinghtml\t2.0.0\n",
       "sphinxcontrib-qthelp\t2.0.0\n",
       "asttokens\t3.0.0\n",
       "kiwisolver\t1.4.9\n",
       "tqdm\t4.67.1\n",
       "executing\t2.2.1\n",
       "psutil\t7.1.0\n",
       "pillow\t11.3.0\n",
       "charset-normalizer\t3.4.3\n",
       "wcwidth\t0.2.13\n",
       "igraph\t0.11.9\n",
       "scikit-learn\t1.7.2\n",
       "session-info2\t0.2.2\n",
       "prompt_toolkit\t3.0.52\n",
       "leidenalg\t0.10.2\n",
       "jupyter_client\t8.6.3\n",
       "----\t----\n",
       "Python\t3.13.7 (main, Aug 15 2025, 12:34:02) [GCC 15.2.1 20250813]\n",
       "OS\tLinux-6.16.8-zen1-1-zen-x86_64-with-glibc2.42\n",
       "CPU\t16 logical CPU cores\n",
       "GPU\tNo GPU found\n",
       "Updated\t2025-09-22 08:42"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from __future__ import annotations\n",
    "\n",
    "import zipfile\n",
    "\n",
    "import pooch\n",
    "\n",
    "import scanpy as sc\n",
    "\n",
    "sc.logging.print_header()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "p_zip = pooch.retrieve(\n",
    "    \"https://www.dropbox.com/s/3dby3bjsaf5arrw/cell_cycle_vignette_files.zip?dl=1\",\n",
    "    known_hash=\"sha256:6557fe2a2761d1550d41edf61b26c6d5ec9b42b4933d56c3161164a595f145ab\",\n",
    "    path=\"../data\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load cell cycle genes defined in [Tirosh et al, 2015](https://doi.org/10.1126/science.aad0501).\n",
    "It is a list of 97 genes, represented by their gene symbol. The list here is for humans, in case of alternate organism, a list of ortologues should be compiled.\n",
    "There are major differences in the way _Scanpy_ and _Seurat_ manage data, in particular we need to filter out cell cycle genes that are not present in our dataset to avoid errors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "with zipfile.ZipFile(p_zip, \"r\") as f_zip:\n",
    "    f_csv = zipfile.Path(f_zip, \"nestorawa_forcellcycle_expressionMatrix.txt\").open()\n",
    "    adata = sc.read_csv(f_csv, delimiter=\"\\t\").T\n",
    "    cell_cycle_genes = (\n",
    "        zipfile.Path(f_zip, \"regev_lab_cell_cycle_genes.txt\").read_text().splitlines()\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we define two lists, genes associated to the S phase and genes associated to the G2M phase"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "s_genes = [x for x in cell_cycle_genes[:43] if x in adata.var_names]\n",
    "g2m_genes = [x for x in cell_cycle_genes[43:] if x in adata.var_names]\n",
    "cell_cycle_genes = [*s_genes, *g2m_genes]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Standard filters applied. Note that we do not extract variable genes and work on the whole dataset, instead. This is because, for this demo, almost 70 cell cycle genes would not be scored as variable. Cell cycle scoring on ~20 genes is ineffective. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "sc.pp.filter_cells(adata, min_genes=200)\n",
    "sc.pp.filter_genes(adata, min_cells=3)\n",
    "sc.pp.normalize_total(adata, target_sum=1e4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Log-transformation of data and scaling should always be performed before scoring"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.pp.log1p(adata)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We here perform cell cycle scoring.\n",
    "The function is actually a wrapper to {func}`scanpy.tl.score_genes`, which is launched twice, to score separately S and G2M phases.\n",
    "Both {func}`scanpy.tl.score_genes` and {func}`scanpy.tl.score_genes_cell_cycle` are a port from _Seurat_ and are supposed to work in a very similar way. \n",
    "To score a gene list, the algorithm calculates the difference of mean expression of the given list and the mean expression of reference genes.\n",
    "To build the reference, the function randomly chooses a bunch of genes matching the distribution of the expression of the given list.\n",
    "Cell cycle scoring adds three slots in data, a score for S phase, a score for G2M phase and the predicted cell cycle phase."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "sc.tl.score_genes_cell_cycle(adata, s_genes=s_genes, g2m_genes=g2m_genes)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here comes another difference from _Seurat_.\n",
    "The R package stores raw data, scaled data and variable genes information in separate slots, _Scanpy_ instead keeps only one snapshot of the data.\n",
    "This implies that PCA is always calculated on the entire dataset. In order to calculate PCA reduction using only a subset of genes (like `cell_cycle_genes`), a trick should be used.\n",
    "Basically we create a dummy object to store information of PCA projection, which is then reincorporated into original dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "adata_cc_genes = adata[:, cell_cycle_genes].copy()\n",
    "sc.tl.pca(adata_cc_genes)\n",
    "sc.pl.pca(adata_cc_genes, color=\"phase\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As in the original vignette, cells can be easily separated by their cell cycle status when cell cycle genes are used.\n",
    "Now we can regress out both S score and G2M score."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "sc.pp.regress_out(adata, [\"S_score\", \"G2M_score\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we reproject dataset using cell cycle genes again. Since we regressed the scores, no effect of cell cycle is now evident."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "adata_cc_genes = adata[:, cell_cycle_genes].copy()\n",
    "sc.tl.pca(adata_cc_genes)\n",
    "sc.pl.pca(adata_cc_genes, color=\"phase\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
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