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   "cell_type": "markdown",
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   "source": [
    "# Clustergrammer Widget\n",
    "\n",
    "## Gene Expression Example\n",
    "This example shows how to visualize a matrix of gene expression data saved as a tab-separated-file (e.g. [rc_two_cats.txt](https://github.com/MaayanLab/clustergrammer-widget/blob/master/rc_two_cats.txt)) using the Clustergrammer interactive widget (see the Clustergrammer Jupyter Widget [Documentation](http://clustergrammer.readthedocs.io/clustergrammer_widget.html) for more information)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# import widget classes and instantiate Network instance\n",
    "from clustergrammer_widget import *\n",
    "net = Network(clustergrammer_widget)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ipywidgets\n",
    "ipywidgets.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import widgetsnbextension\n",
    "widgetsnbextension.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load matrix file\n",
    "net.load_file('rc_two_cats.txt')\n",
    "\n",
    "# cluster using default parameters\n",
    "net.cluster(enrichrgram=True)\n",
    "\n",
    "# make interactive widget\n",
    "net.widget()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": []
  }
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