notebooks/get_isa_and_partof.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# How to get GO IDs up both the '_is a_' and '_part of_' relationships\n",
    "\n",
    "  1. Download Ontologies, if necessary\n",
    "  2. Choose a set of GO IDs to print\n",
    "  3. GO colors for plotting\n",
    "  4. Traverse up or down the GO DAG with no, all, or some optional relationships(a):\n",
    "    * 4a) No optional relationships, like **part_of** and **regulates**\n",
    "    * 4b) All relationships\n",
    "    * 4c) Relationship: **part_of**\n",
    "    * 4d) Relationship: **regulates**\n",
    "    * 4e) Relationship: **positively_regulates**\n",
    "    * 4f) Relationship: **negatively_regulates**\n",
    " \n",
    " \n",
    "a) The *is_a* relationships will always be traversed to find the children or parents of a GO term\n",
    "\n",
    "## Plots with and without relationships\n",
    "\n",
    "Arrows denote the relationships, *is_a* (solid black arrows) and *part_of* (dashed orange arrows), in the plots below: \n",
    "\n",
    "| With no optional relationships  | With the optional *part_of* relationship\n",
    "|---------------------------------|-------------------------------\n",
    "|  ![is_a](images/fig1_r0.png)    | ![part_of](images/fig1_r1.png)  \n",
    "\n",
    "Notice that the text in the GO term box is different if you are plotting using optional relationships. The bottom GO term text is:\n",
    "\n",
    "* Left plot: **GO:0043231 L3 D3 d0**\n",
    "* Right plot: **GO:0043231 D3 R4 d0**\n",
    "\n",
    "**L (Level)** is the minimum distance from root term, *cellular_component*, to the bottom term    \n",
    "**D (Depth)**, is the maximum distance from root term, *cellular_component*, to the bottom term using only *is_a* relationships  \n",
    "**R (Depth using optional relationships)**, is the maximum distance from root term, *cellular_component*, to the bottom term using both *is_a* and optional relationships\n",
    "\n",
    "In this example **D (Depth)** from the root to the bottom term is 3 (light blue lines).    \n",
    "\n",
    "And **R (Depth using optional relationships)** from the root to the bottom is 4 (dark purple lines) because it traverses the *part_of* relationships\n",
    "\n",
    "<img src=\"images/fig1_depth_marked.png\" alt=\"depth explained\" width=\"450\">\n",
    "  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Download Ontologies, if necessary\n",
    "Load all relationships into a GODag object.       \n",
    "Specific relationships, like **part_of** or **regulates**, will be chosen using GoSubDag.    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "requests.get(http://purl.obolibrary.org/obo/go/go-basic.obo, stream=True)\n",
      "  WROTE: go-basic.obo\n",
      "\n",
      "go-basic.obo: fmt(1.2) rel(2020-12-08) 47,295 GO Terms; optional_attrs(relationship)\n",
      "  EXISTS: ../tests/data/i126/viral_gene_silence.obo\n",
      "../tests/data/i126/viral_gene_silence.obo: fmt(1.2) rel(2019-04-17) 79 GO Terms; optional_attrs(relationship)\n"
     ]
    }
   ],
   "source": [
    "from goatools.base import get_godag\n",
    "godag = get_godag(\"go-basic.obo\", optional_attrs={'relationship'})\n",
    "\n",
    "# We are going to use a GO DAG subset for this example\n",
    "godag = get_godag(\"../tests/data/i126/viral_gene_silence.obo\", optional_attrs={'relationship'})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Choose a set of GO IDs to print\n",
    "This example will use all GO IDs above GO:0060150, *viral triggering of virus induced gene silencing*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "virus_trigger_silence = 'GO:0060150'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. GO colors\n",
    "The GO DAG and go-color files for this example are located in: **./tests/data/i126**   \n",
    "\n",
    "GO colors are stored in **viral_gene_silence.txt** as 6-digit hax numbers, like #ffe5b4.    \n",
    "The color file looks like this:\n",
    "```\n",
    "Relationship, part_of, shall be orange (#ffe5b4):\n",
    "#ffe5b4 GO:0002376 immune system process\n",
    "#ffe5b4 GO:0050896 response to stimulus\n",
    "#ffe5b4 GO:0051704 multi-organism process\n",
    "...\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from goatools.cli.gos_get import get_go2color\n",
    "\n",
    "go2hexcolor = get_go2color('../tests/data/i126/viral_gene_silence.txt')\n",
    "\n",
    "# For printing GO terms and their color names to the print\n",
    "hex2color = {\n",
    "    '#e6fad2': 'green',\n",
    "    '#ffe5b4': 'orange',\n",
    "    '#d2d2fa': 'purple',\n",
    "    '#d2fafa': 'cyan',\n",
    "    '#fad2fa': 'magenta',\n",
    "    '#d8dcd6': 'grey',\n",
    "}\n",
    "GREY = '#d8dcd6'\n",
    "GO2COLORNAME = {go: hex2color[rgb] for go, rgb in go2hexcolor.items()}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Traversals up the GO DAG\n",
    "### 4a. No optional relationships loaded\n",
    "Do not traverse any optional relationships, like **part_of** and **regulates**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " GoSubDag:   1 sources in  13 GOs rcnt(True). 0 alt GO IDs\n",
      " GoSubDag: namedtuple fields: NS level depth GO alt GO_name dcnt D1 id\n",
      " GoSubDag: relationships: set()\n"
     ]
    }
   ],
   "source": [
    "from goatools.gosubdag.gosubdag import GoSubDag\n",
    "\n",
    "gosubdag_r0 = GoSubDag({virus_trigger_silence}, godag)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NtGo(NS='BP', level=5, depth=8, GO='GO:0060148', alt='', GO_name='positive regulation of posttranscriptional gene silencing', dcnt=1, D1='A', id='GO:0060148')\n"
     ]
    }
   ],
   "source": [
    "# Decide which GO fields to print. Save in prtfmt\n",
    "\n",
    "# Print one namedtuple\n",
    "print(next(iter(gosubdag_r0.go2nt.values())))\n",
    "\n",
    "# Use some namedtuple fields in print of GO terms\n",
    "PRTFMT = '{NS} {GO} D-{depth:02} {color:7} {dcnt:2} {GO_name}'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BP GO:0008150 D-00 green   50 biological_process\n",
      "BP GO:0065007 D-01 green   19 biological regulation\n",
      "BP GO:0050789 D-02 green   18 regulation of biological process\n"
     ]
    }
   ],
   "source": [
    "# Report all ancestors of term, GO:001922 (colored grey)\n",
    "grey_go = 'GO:0019222'\n",
    "ancestors = gosubdag_r0.rcntobj.go2ancestors[grey_go]\n",
    "\n",
    "def prt_goids(goids, gosubdag):\n",
    "    \"\"\"Print GO IDs\"\"\"\n",
    "    nts = [gosubdag.go2nt[go] for go in goids]\n",
    "    for nt_go in sorted(nts, key=lambda nt: [nt.depth, nt.dcnt]):\n",
    "        color = GO2COLORNAME[nt_go.GO]\n",
    "        print(PRTFMT.format(color=color, **nt_go._asdict()))\n",
    "\n",
    "prt_goids(ancestors, gosubdag_r0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot no optional relationships, just using ***is_a*** (runtime script):\n",
    "Color the term, GO:0019222 *regulation of metabolic process*, with xkcd's *light grey* (#d8dcd6)\n",
    "\n",
    "```\n",
    "$ go_plot.py -o viral_r0.png GO:0060150 GO:0019222#d8dcd6 --obo=viral_gene_silence.obo --go_color_file=viral_gene_silence.txt\n",
    "\n",
    "```\n",
    "<img src=\"images/viral_r0.png\" width=\"900pt\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot no optional relationships, just using ***is_a*** (code):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    1 usr  13 GOs  WROTE: viral_r0.png\n"
     ]
    }
   ],
   "source": [
    "from goatools.gosubdag.plot.gosubdag_plot import GoSubDagPlot\n",
    "\n",
    "# Color the GO of interest in a copy of the color dictionary\n",
    "go2col = dict(go2hexcolor)\n",
    "go2col[grey_go] = GREY\n",
    "\n",
    "pltobj = GoSubDagPlot(gosubdag_r0, go2color=go2col)\n",
    "pltobj.plt_dag('viral_r0.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4b. All relationships\n",
    "Traverse all optional relationships, like **part_of** and **regulates**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " GoSubDag:   1 sources in  51 GOs rcnt(True). 0 alt GO IDs\n",
      " GoSubDag: namedtuple fields: NS level depth reldepth GO alt GO_name dcnt D1 childcnt REL REL_short rel id\n",
      " GoSubDag: relationships: {'negatively_regulates', 'regulates', 'part_of', 'positively_regulates'}\n",
      "BP GO:0008150 D-00 green   50 biological_process\n",
      "BP GO:0008152 D-01 cyan    17 metabolic process\n",
      "BP GO:0065007 D-01 green   19 biological regulation\n",
      "BP GO:0071704 D-02 purple  14 organic substance metabolic process\n",
      "BP GO:0050789 D-02 green   18 regulation of biological process\n",
      "BP GO:0019222 D-03 green   13 regulation of metabolic process\n",
      "BP GO:0043170 D-03 cyan    13 macromolecule metabolic process\n",
      "BP GO:0010467 D-04 cyan    10 gene expression\n",
      "BP GO:0060255 D-04 green   11 regulation of macromolecule metabolic process\n"
     ]
    }
   ],
   "source": [
    "gosubdag_r1 = GoSubDag({virus_trigger_silence}, godag, relationships=True)\n",
    "\n",
    "# Report all ancestors of grey term\n",
    "grey_go = 'GO:0010468'  # regulation of gene expression\n",
    "ancestors = gosubdag_r1.rcntobj.go2ancestors[grey_go]\n",
    "prt_goids(ancestors, gosubdag_r1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot **all** relationships (runtime script):\n",
    "\n",
    "```\n",
    "$ go_plot.py -o viral_r1.png -r GO:0060150 GO:0010468#d8dcd6 --obo=viral_gene_silence.obo --go_color_file=viral_gene_silence.txt\n",
    "```\n",
    "<img src=\"images/viral_r1.png\" width=\"2000pt\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot **all** relationships (code):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    1 usr  51 GOs  WROTE: viral_r1.png\n"
     ]
    }
   ],
   "source": [
    "# Color the GO of interest in a copy of the color dictionary\n",
    "go2col = dict(go2hexcolor)\n",
    "go2col[grey_go] = GREY\n",
    "\n",
    "pltobj = GoSubDagPlot(gosubdag_r1, go2color=go2col)\n",
    "pltobj.plt_dag('viral_r1.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4c. Relationship: *part_of*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " GoSubDag:   1 sources in  38 GOs rcnt(True). 0 alt GO IDs\n",
      " GoSubDag: namedtuple fields: NS level depth reldepth GO alt GO_name dcnt D1 childcnt REL REL_short rel id\n",
      " GoSubDag: relationships: {'part_of'}\n",
      "BP GO:0008150 D-00 green   50 biological_process\n",
      "BP GO:0065007 D-01 green   19 biological regulation\n",
      "BP GO:0050789 D-02 green   18 regulation of biological process\n",
      "BP GO:0019222 D-03 green   13 regulation of metabolic process\n",
      "BP GO:0060255 D-04 green   11 regulation of macromolecule metabolic process\n"
     ]
    }
   ],
   "source": [
    "gosubdag_partof = GoSubDag({virus_trigger_silence}, godag, relationships={'part_of',})\n",
    "\n",
    "# Report all ancestors of grey term\n",
    "grey_go = 'GO:0010468'  # regulation of gene expression\n",
    "ancestors = gosubdag_partof.rcntobj.go2ancestors[grey_go]\n",
    "prt_goids(ancestors, gosubdag_partof)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot ***part_of*** relationships (runtime script):    \n",
    "Orange dashed lines represent *part_of* relationships:\n",
    "\n",
    "```\n",
    "$ go_plot.py -o viral_r_partof.png --relationships=part_of GO:0010468#d8dcd6 GO:0060150 --obo=viral_gene_silence.obo --go_color_file=viral_gene_silence.txt \n",
    "```\n",
    "<img src=\"images/viral_r_partof.png\" width=\"900pt\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot ***part_of*** relationships (code)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    1 usr  38 GOs  WROTE: viral_r_partof.png\n"
     ]
    }
   ],
   "source": [
    "# Color the GO of interest in a copy of the color dictionary\n",
    "go2col = dict(go2hexcolor)\n",
    "go2col[grey_go] = GREY\n",
    "\n",
    "pltobj = GoSubDagPlot(gosubdag_partof, go2color=go2col)\n",
    "pltobj.plt_dag('viral_r_partof.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4d. Relationship: *regulates*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " GoSubDag:   1 sources in  26 GOs rcnt(True). 0 alt GO IDs\n",
      " GoSubDag: namedtuple fields: NS level depth reldepth GO alt GO_name dcnt D1 childcnt REL REL_short rel id\n",
      " GoSubDag: relationships: {'regulates'}\n",
      "BP GO:0008150 D-00 green   50 biological_process\n",
      "BP GO:0009987 D-01 magenta  8 cellular process\n",
      "BP GO:0065007 D-01 green   19 biological regulation\n",
      "BP GO:0050789 D-02 green   18 regulation of biological process\n"
     ]
    }
   ],
   "source": [
    "gosubdag_reg = GoSubDag({virus_trigger_silence}, godag, relationships={'regulates',})\n",
    "\n",
    "# Report all ancestors of grey term\n",
    "grey_go = 'GO:0050794'  # regulation of cellular process\n",
    "ancestors = gosubdag_reg.rcntobj.go2ancestors[grey_go]\n",
    "prt_goids(ancestors, gosubdag_reg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot ***regulates*** relationships (runtime script):    \n",
    "Purple dashed lines represent *regulates* relationships:\n",
    "\n",
    "```\n",
    "$ go_plot.py -o viral_reg.png --relationships=regulates GO:0050794#d8dcd6 GO:0060150 --obo=viral_gene_silence.obo --go_color_file=viral_gene_silence.txt \n",
    "```\n",
    "<img src=\"images/viral_reg.png\" width=\"900pt\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot ***regulates*** relationships (code):    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    1 usr  26 GOs  WROTE: viral_reg.png\n"
     ]
    }
   ],
   "source": [
    "# Color the GO of interest in a copy of the color dictionary\n",
    "go2col = dict(go2hexcolor)\n",
    "go2col[grey_go] = GREY\n",
    "\n",
    "pltobj = GoSubDagPlot(gosubdag_reg, go2color=go2col)\n",
    "pltobj.plt_dag('viral_reg.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4e. Relationship: *positively_regulates*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " GoSubDag:   1 sources in  22 GOs rcnt(True). 0 alt GO IDs\n",
      " GoSubDag: namedtuple fields: NS level depth reldepth GO alt GO_name dcnt D1 childcnt REL REL_short rel id\n",
      " GoSubDag: relationships: {'positively_regulates'}\n"
     ]
    }
   ],
   "source": [
    "gosubdag_regp = GoSubDag({virus_trigger_silence}, godag, relationships={'positively_regulates',})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BP GO:0008150 D-00 green   50 biological_process\n",
      "BP GO:0009987 D-01 magenta  5 cellular process\n",
      "BP GO:0065007 D-01 green   19 biological regulation\n",
      "BP GO:0050789 D-02 green   18 regulation of biological process\n",
      "BP GO:0048518 D-03 green    3 positive regulation of biological process\n",
      "BP GO:0050794 D-03 green    5 regulation of cellular process\n"
     ]
    }
   ],
   "source": [
    "# Report all ancestors of grey term\n",
    "grey_go = 'GO:0048522'  # positive regulation of cellular process\n",
    "ancestors = gosubdag_regp.rcntobj.go2ancestors[grey_go]\n",
    "prt_goids(ancestors, gosubdag_regp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot ***positively_regulates*** relationships (runtime script):    \n",
    "Magenta dashed lines represent *positively regulates* relationships:    \n",
    "\n",
    "```\n",
    "$ go_plot.py -o viral_rp.png --relationships=positively_regulates GO:0048522#d8dcd6 GO:0060150 --obo=viral_gene_silence.obo --go_color_file=viral_gene_silence.txt \n",
    "```\n",
    "<img src=\"images/viral_rp.png\" width=\"900pt\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot ***positively_regulates*** relationships (code):    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    1 usr  22 GOs  WROTE: viral_rp.png\n"
     ]
    }
   ],
   "source": [
    "# Color the GO of interest in a copy of the color dictionary\n",
    "go2col = dict(go2hexcolor)\n",
    "go2col[grey_go] = GREY\n",
    "\n",
    "pltobj = GoSubDagPlot(gosubdag_regp, go2color=go2col)\n",
    "pltobj.plt_dag('viral_rp.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4f. Relationship: *negatively_regulates*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " GoSubDag:   1 sources in  26 GOs rcnt(True). 0 alt GO IDs\n",
      " GoSubDag: namedtuple fields: NS level depth reldepth GO alt GO_name dcnt D1 childcnt REL REL_short rel id\n",
      " GoSubDag: relationships: {'negatively_regulates', 'regulates'}\n",
      "BP GO:0008150 D-00 green   50 biological_process\n",
      "BP GO:0009987 D-01 magenta  8 cellular process\n",
      "BP GO:0065007 D-01 green   19 biological regulation\n",
      "BP GO:0050789 D-02 green   18 regulation of biological process\n"
     ]
    }
   ],
   "source": [
    "gosubdag_regn = GoSubDag({virus_trigger_silence}, godag, relationships={'regulates', 'negatively_regulates',})\n",
    "\n",
    "# Report all ancestors of grey term\n",
    "grey_go = 'GO:0050794'  # regulation of cellular process\n",
    "ancestors = gosubdag_regn.rcntobj.go2ancestors[grey_go]\n",
    "prt_goids(ancestors, gosubdag_regn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot ***negatively_regulates*** relationships (runtime script):    \n",
    "Cyan dashed lines represent *negatively regulates* relationships    \n",
    "\n",
    "**NOTE:** In this example, the following *relationships* argument will have **no affect** because **no green GO IDs** have the relationship, *negatively_regulates*:    \n",
    "**--relationships=*negatively_regulates***\n",
    "\n",
    "\n",
    "To see *negatively_regulates*, specify both *regulates* and *negatively_regulates*:    \n",
    "**--relationships=*regulates,negatively_regulates***\n",
    "\n",
    "Note that specifying both *regulates* and *negatively_regulates* will case the magenta GO IDs to be traversed. The magenta GO IDs are accessed by both the *regulates* and the *positively_regulates* relationships.\n",
    "\n",
    "```\n",
    "$ go_plot.py -o viral_rn.png --relationships=regulates,negatively_regulates GO:0050794#d8dcd6 GO:0060150 --obo=viral_gene_silence.obo --go_color_file=viral_gene_silence.txt\n",
    "```\n",
    "<img src=\"images/viral_rn.png\" width=\"900pt\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot ***negatively_regulates*** relationships (code):    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    1 usr  26 GOs  WROTE: viral_rn.png\n"
     ]
    }
   ],
   "source": [
    "# Color the GO of interest in a copy of the color dictionary\n",
    "go2col = dict(go2hexcolor)\n",
    "go2col[grey_go] = GREY\n",
    "\n",
    "pltobj = GoSubDagPlot(gosubdag_regn, go2color=go2col)\n",
    "pltobj.plt_dag('viral_rn.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Copyright (C) 2016-present, DV Klopfenstein et al. All rights reserved"
   ]
  }
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