Course GEM and FBA_2 Metabolic pathway visualizations with Escher.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
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   "source": [
    "# 2. Metabolic pathway visualizations with Escher\n",
    "\n",
    "## Escher Python tutorial\n",
    "\n",
    "The Escher Python package makes it easy to run and customize Escher visualizations from within a Jupyter Notebook or Jupyter lab. The Python package also works directly with COBRApy models. This tutorial introduces the main features. It is also a runnable notebook, which you can download here:\n",
    "\n",
    "https://github.com/zakandrewking/escher/blob/master/docs/escher-python.ipynb\n",
    "\n",
    "Once Escher and the appropriate extension are installed (next section), you should be able to run this notebook in Jupyter Notebook or Jupyter Lab.\n",
    "\n",
    "If you don't use Jupyter, you can also save standalone visualizations as HTML files using Escher Python. An example is included at the end of the tutorial."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Installation\n",
    "\n",
    "You can install Escher Python with pip:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
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      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install pytest-astropy"
   ]
  },
  {
   "cell_type": "code",
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      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install escher"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When you pip install escher, the Jupyter notebook extension should be installed automatically. If that doesn't work, try:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "invalid syntax (<ipython-input-3-ba8fea5f4284>, line 2)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;36m  File \u001b[1;32m\"<ipython-input-3-ba8fea5f4284>\"\u001b[1;36m, line \u001b[1;32m2\u001b[0m\n\u001b[1;33m    jupyter nbextension list\u001b[0m\n\u001b[1;37m                      ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m invalid syntax\n"
     ]
    }
   ],
   "source": [
    "# The notebook extenstion should install automatically. You can check by running:\n",
    "jupyter nbextension list\n",
    "# Make sure you have version >=5 of the `notebook` package\n",
    "pip install \"notebook>=5\"\n",
    "# To manually install the extension\n",
    "jupyter nbextension install --py escher\n",
    "jupyter nbextension enable --py escher\n",
    "# depending on you environment, you might need the `--sysprefix` flag with those commands"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you have issues, you can leave a bug report on GitHub or ask for help on Gitter."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load an Escher map\n",
    "### To get started, we'll import Escher and COBRApy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import escher\n",
    "from escher import Builder\n",
    "import cobra\n",
    "from time import sleep"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Global configuration\n",
    "\n",
    "Escher currently offers on global configuration option. We will consider adding more in the future. This option turns off the warning message if you leave or refresh this page. The default setting is False to help you avoid losing work."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "escher.rc['never_ask_before_quit'] = True"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For most of this tutorial, all you need is the Builder class from escher."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The Builder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "builder = Builder()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Builder is a Jupyter widget, so executing it in a cell will run the widget and embed an Escher map. You should see an empty Escher map in the next cell"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1c3c0c0b886a4e90bf7baa7215fc4955",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Builder(never_ask_before_quit=True)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "builder"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Finding models and maps\n",
    "\n",
    "But the Builder isn't very useful without some data!\n",
    "\n",
    "In general, Escher is meant for building your own maps. Maps are generated with the content of genome-scale models, and you can find many models to explore on the BiGG Models database: http://bigg.ucsd.edu\n",
    "\n",
    "Let's download the red blood cell model iAB_RBC_283."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = 'iAB_RBC_283.json'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can add this model to the Escher Builder with the model_json option."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "builder = Builder(\n",
    "    model_json=model\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, in the following map, click \"Edit > Add reaction mode\" and click anywhere to start drawing reactions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c8eda96d7e9b467e83041763d0857bcb",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Builder(never_ask_before_quit=True)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "builder"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Later, you can save this map by clicking \"Map > Save map JSON\", and you can load JSON files in a Builder with the map_json option."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### TIP: You can jump into full-screen mode by clicking the button on the map¶\n",
    "In full-screen mode, keyboard shortcuts, mouse scrolling, and trackpad interactions are all activated.\n",
    "\n",
    "To leave full-screen mode, press the escape key or click again."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Maps and models from the Escher website¶\n",
    "\n",
    "Testing and getting started, Escher also provides a few default maps and models. You can see which ones are available with the following functions. To use a map or model, pass the name to the Builder options map_name and model_name."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'organism': 'Saccharomyces cerevisiae',\n",
       "  'map_name': 'iMM904.Central carbon metabolism'},\n",
       " {'organism': 'Homo sapiens',\n",
       "  'map_name': 'RECON1.Inositol retinol metabolism'},\n",
       " {'organism': 'Homo sapiens', 'map_name': 'RECON1.Glycolysis TCA PPP'},\n",
       " {'organism': 'Homo sapiens', 'map_name': 'RECON1.Tryptophan metabolism'},\n",
       " {'organism': 'Homo sapiens', 'map_name': 'RECON1.Carbohydrate metabolism'},\n",
       " {'organism': 'Homo sapiens',\n",
       "  'map_name': 'RECON1.Amino acid metabolism (partial)'},\n",
       " {'organism': 'Escherichia coli', 'map_name': 'iJO1366.Nucleotide metabolism'},\n",
       " {'organism': 'Escherichia coli',\n",
       "  'map_name': 'iJO1366.Fatty acid biosynthesis (saturated)'},\n",
       " {'organism': 'Escherichia coli',\n",
       "  'map_name': 'iJO1366.Nucleotide and histidine biosynthesis'},\n",
       " {'organism': 'Escherichia coli', 'map_name': 'e_coli_core.Core metabolism'},\n",
       " {'organism': 'Escherichia coli', 'map_name': 'iJO1366.Central metabolism'},\n",
       " {'organism': 'Escherichia coli',\n",
       "  'map_name': 'iJO1366.Fatty acid beta-oxidation'}]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "escher.list_available_maps()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'organism': 'Saccharomyces cerevisiae', 'model_name': 'iMM904'},\n",
       " {'organism': 'Homo sapiens', 'model_name': 'RECON1'},\n",
       " {'organism': 'Escherichia coli', 'model_name': 'e_coli_core'},\n",
       " {'organism': 'Escherichia coli', 'model_name': 'iJO1366'}]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "escher.list_available_models()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can load these maps and models by specifying map_name and model_name."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading Map from https://escher.github.io/1-0-0/6/maps/Escherichia%20coli/e_coli_core.Core%20metabolism.json\n",
      "Downloading Model from https://escher.github.io/1-0-0/6/models/Escherichia%20coli/e_coli_core.json\n"
     ]
    }
   ],
   "source": [
    "builder = Builder(\n",
    "    map_name='e_coli_core.Core metabolism',\n",
    "    model_name='e_coli_core',\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "71f86c176af84a2ab9d35e3b4aa40570",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Builder(never_ask_before_quit=True)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "builder"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reactive options\n",
    "\n",
    "The Escher Builder is a \"reactive\" widget, so it will update automatically when you change data and options. Let's create another empty builder."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "builder=Builder()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "36638213511b496d8e24ff7a7c40a625",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Builder(never_ask_before_quit=True)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "builder"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And this time, try running some of the following cells and look at the response in the map above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading Map from https://escher.github.io/1-0-0/6/maps/Escherichia%20coli/iJO1366.Central%20metabolism.json\n"
     ]
    }
   ],
   "source": [
    "# Load an Escher map\n",
    "builder.map_name = 'iJO1366.Central metabolism'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading Model from https://escher.github.io/1-0-0/6/models/Escherichia%20coli/e_coli_core.json\n"
     ]
    }
   ],
   "source": [
    "# Load a COBRA model\n",
    "builder.model_name = 'e_coli_core'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Find any reactions that are in the map and not in the model, and turn them red\n",
    "builder.highlight_missing = True"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "COBRA models are available directly from BiGG Models. Download a model from BiGG in the JSON format and read it with COBRApy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "builder.model = cobra.io.load_json_model('iJO1366.json')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Run FBA with the model and add the flux data to the map\n",
    "solution = builder.model.optimize()\n",
    "builder.reaction_data = solution.fluxes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add some data for metabolites\n",
    "builder.metabolite_data = solution.shadow_prices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Simplify the map by hiding some labels\n",
    "builder.hide_secondary_metabolites = True\n",
    "builder.hide_all_labels = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "builder.reaction_scale = [\n",
    "    { 'type': 'min', 'color': '#000000', 'size': 12 },\n",
    "    { 'type': 'median', 'color': '#ffffff', 'size': 20 },\n",
    "    { 'type': 'max', 'color': '#ff0000', 'size': 25 }\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "builder.reaction_scale_preset = 'GaBuRd'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Make all the arrows three times as thick\n",
    "builder.reaction_scale = [\n",
    "    {k: v * 3 if k == 'size' else v for k, v in x.items()} \n",
    "    for x in builder.reaction_scale\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# some other things to try:\n",
    "# builder.scroll_behavior = 'zoom'\n",
    "# builder.reaction_styles = ['size']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### All options\n",
    "\n",
    "The full list of options is provided in the Python API documentation:\n",
    "\n",
    "https://escher.readthedocs.io/en/latest/python_api.html\n",
    "\n",
    "For more-detailed descriptions of the Keyword Arguments, you can also refer to the JavaScript API docs:\n",
    "\n",
    "https://escher.readthedocs.io/en/latest/javascript_api.html"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Advanced: Make an animation\n",
    "With reactive options, you can easily implement animations in an Escher map. Here's a simple example where flux predictions are swept across and range to update the map of E. coli core metabolism."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading Model from https://escher.github.io/1-0-0/6/models/Escherichia%20coli/e_coli_core.json\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "73f368bb32294334a3fef7fcb0094e2d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Builder(height=600, never_ask_before_quit=True)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "builder = Builder(\n",
    "    height=600, \n",
    "    map_name=None, \n",
    "    model_name='e_coli_core',\n",
    "    map_json='https://escher.github.io/1-0-0/5/maps/Escherichia%20coli/e_coli_core.Core%20metabolism.json',\n",
    ")\n",
    "builder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = cobra.io.load_json_model('e_coli_core.json')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "cobra\\util\\solver.py:416 UserWarning: solver status is 'infeasible'\n"
     ]
    }
   ],
   "source": [
    "reverse = False\n",
    "step = 0.1\n",
    "timestep = 0.1\n",
    "duration = 15 # seconds\n",
    "lim = [0, 0.5]\n",
    "val = lim[-1]\n",
    "for _ in range(int(duration / timestep)):\n",
    "    model.reactions.EX_o2_e.lower_bound = -val\n",
    "    solution = model.optimize()\n",
    "    builder.reaction_data = solution.fluxes\n",
    "    if val <= lim[0]:\n",
    "        reverse = True\n",
    "    if val >= lim[1]:\n",
    "        reverse = False\n",
    "    if reverse:\n",
    "        val += step\n",
    "    else:\n",
    "        val -= step\n",
    "    sleep(timestep)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Saving maps as HTML\n",
    "The Escher Builder can also be saved as a standalone HTML file, which you can view by opening in a browser. Just provide a filepath, and the map will be bundled along with all the current options."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "builder.save_html('example_map.html')"
   ]
  }
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