{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "source": [
    "# Biopython continued\n",
    "## 09/26/2023\n",
    "\n",
    "<a href=\"?print-pdf\">print view</a><br>\n",
    "<a href=\"seqcont.ipynb\">notebook</a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<script src=\"https://bits.csb.pitt.edu/preamble.js\"></script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%html\n",
    "<script src=\"https://bits.csb.pitt.edu/preamble.js\"></script>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "source": [
    "# Sequence Project\n",
    "\n",
    "https://MSCBIO.github.io/files/hydra179.aln\n",
    "\n",
    "Identify the region of this gene with the most variation.\n",
    "\n",
    "1. For each position, identify and plot the number of unique residues\n",
    "2. For each position, identify and plot the number of unique subsequences of length 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from Bio import AlignIO\n",
    "\n",
    "def countatpos(seqs,pos):\n",
    "    '''count the number of unique subsequences of length 10 at pos in seqs'''\n",
    "    vals = set()\n",
    "    for s in seqs:\n",
    "        vals.add(str(s[pos:pos+10].seq))\n",
    "    return len(vals)\n",
    "\n",
    "seqs = AlignIO.read(\"../files/hydra179.aln\",'clustal');\n",
    "\n",
    "xaxis = list()\n",
    "yaxis = list()\n",
    "for i in range(seqs.get_alignment_length()):\n",
    "    xaxis.append(i)\n",
    "    yaxis.append(countatpos(seqs,i))\n",
    "\n",
    "plt.bar(xaxis,yaxis,width=1);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "source": [
    "<img src=\"imgs/sequence_project/sequence_project.011.png\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "source": [
    "# A bit more python... list comprehensions\n",
    "\n",
    "A concise way to create lists\n",
    "\n",
    "`[ <expr of var> for <var> in <iterable> if <condition> ]`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 2, 4, 6, 8]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[x for x in range(10) if x % 2 == 0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "source": [
    "# Three ways to do the same thing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "squares = [x**2 for x in range(10)]\n",
    "squares"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "squares = []\n",
    "for x in range(10):\n",
    "    squares.append(x**2)\n",
    "squares"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "squares = list(map(lambda x: x**2, range(10)))\n",
    "squares"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "source": [
    "# Other comprehensions\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0, 'A'), (1, 'B'), (2, 'C'), (3, 'D')]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(enumerate('ABCD')) #enumerate returns tuples of index,value"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "### Dictionary comprehension"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: 'A', 3: 'D'}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "{key: val for key, val in enumerate('ABCD') if val not in 'CB'}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "### Set comprehension"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'A', 'D'}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "{v for v in 'ABCDABCD' if v not in 'CB'}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "source": [
    "# Should you use comprehensions?\n",
    "\n",
    "Sure, if the result is short and easy to understand\n",
    "\n",
    "But don't go out of your way to use them - they can get ugly fast"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "result = [line.strip().split(\"\\t\") for line in open(\"file\") if not line.startswith('#')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div id=\"seq2comp\" style=\"width: 500px\"></div>\n",
       "<script>\n",
       "$('head').append('<link rel=\"stylesheet\" href=\"https://bits.csb.pitt.edu/asker.js/themes/asker.default.css\" />');\n",
       "\n",
       "    var divid = '#seq2comp';\n",
       "\tjQuery(divid).asker({\n",
       "\t    id: divid,\n",
       "\t    question: \"What is in result?\",\n",
       "\t\tanswers: [\"A\",\"B\",\"C\",\"D\",\"E\"],\n",
       "        extra: ['A list of lists of the tab separated values of lines with #',\n",
       "                'A list of lists of the tab separated values of lines without #',\n",
       "                'A list of the lines without #',\n",
       "                'A list of the tab separated values of lines without #',\n",
       "                'I have no idea'],\n",
       "        server: \"https://bits.csb.pitt.edu/asker.js/example/asker.cgi\",\n",
       "\t\tcharter: chartmaker})\n",
       "    \n",
       "$(\".jp-InputArea .o:contains(html)\").closest('.jp-InputArea').hide();\n",
       "\n",
       "\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%html\n",
    "<div id=\"seq2comp\" style=\"width: 500px\"></div>\n",
    "<script>\n",
    "$('head').append('<link rel=\"stylesheet\" href=\"https://bits.csb.pitt.edu/asker.js/themes/asker.default.css\" />');\n",
    "\n",
    "    var divid = '#seq2comp';\n",
    "\tjQuery(divid).asker({\n",
    "\t    id: divid,\n",
    "\t    question: \"What is in result?\",\n",
    "\t\tanswers: [\"A\",\"B\",\"C\",\"D\",\"E\"],\n",
    "        extra: ['A list of lists of the tab separated values of lines with #',\n",
    "                'A list of lists of the tab separated values of lines without #',\n",
    "                'A list of the lines without #',\n",
    "                'A list of the tab separated values of lines without #',\n",
    "                'I have no idea'],\n",
    "        server: \"https://bits.csb.pitt.edu/asker.js/example/asker.cgi\",\n",
    "\t\tcharter: chartmaker})\n",
    "    \n",
    "$(\".jp-InputArea .o:contains(html)\").closest('.jp-InputArea').hide();\n",
    "\n",
    "\n",
    "</script>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "seqs = AlignIO.read(\"../files/hydra179.aln\",'clustal');\n",
    "yaxis = [len({str(s[i:i+10].seq) for s in seqs}) for i in range(seqs.get_alignment_length())]\n",
    "plt.bar(range(seqs.get_alignment_length()),yaxis,width=1);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "source": [
    "# Back to Biopython..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from Bio import AlignIO\n",
    "a = AlignIO.read('../files/hydra179.aln','clustal')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "179"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(706, 706)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(a[0]),a.get_alignment_length()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<<class 'Bio.Align.MultipleSeqAlignment'> instance (179 records of length 706) at 1199dbd00>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "source": [
    "# Phylogenetic Trees\n",
    "\n",
    "*A phylogenetic tree or evolutionary tree is a branching diagram or \"tree\" showing the inferred evolutionary relationships among various biological species or other entities—their phylogeny—based upon similarities and differences in their physical or genetic characteristics.* --Wikipedia\n",
    "\n",
    "Biopython can read a variety of tree formats: **Newick (clustal)**, NEXUS, phyloXML, NeXML, and CDAO."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Tree(rooted=False, weight=1.0)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from Bio import Phylo\n",
    "tree = Phylo.read('../files/hydra179.dnd','newick') #must specify format\n",
    "tree"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "source": [
    "# Displaying trees"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                  ______ gi|302171738|gb|ADK97770.1|\n",
      "             ____|\n",
      "            |    |____ gi|302171740|gb|ADK97771.1|\n",
      "       _____|\n",
      "      |     |                               , gi|313105485|gb|ADR32101.1|\n",
      "      |     |_______________________________|\n",
      "      |                                     | gi|313105490|gb|ADR32105.1|\n",
      "      |\n",
      "      |     , gi|225423246|gb|ACN91129.1|\n",
      "      |     |\n",
      "      |     | gi|407380197|gb|AFU11414.1|\n",
      "      |     |\n",
      "      |     |, gi|302171754|gb|ADK97778.1|\n",
      "      |     ||\n",
      "      |     || gi|407380047|gb|AFU11341.1|\n",
      "      |     |\n",
      "      |    ,, gi|407380097|gb|AFU11366.1|\n",
      "      |    ||\n",
      "      |    || gi|407380101|gb|AFU11368.1|\n",
      "      |    ||\n",
      "      |    || gi|407380017|gb|AFU11326.1|\n",
      "      |    ||\n",
      "      |    || gi|407380135|gb|AFU11385.1|\n",
      "      |    ||\n",
      "      |    || gi|407380117|gb|AFU11376.1|\n",
      "      |    |\n",
      "      |    |, gi|407380023|gb|AFU11329.1|\n",
      "      |    ||\n",
      "      |    || gi|407380045|gb|AFU11340.1|\n",
      "      |    ||\n",
      "      |    || gi|302171762|gb|ADK97782.1|\n",
      "      |    |\n",
      "      |    |_ gi|407380093|gb|AFU11364.1|\n",
      "      |    |\n",
      "      |    | , gi|302171792|gb|ADK97797.1|\n",
      "      |    | |\n",
      "      |    |,| gi|302171794|gb|ADK97798.1|\n",
      "      |    |||\n",
      "      |    ||| gi|225423258|gb|ACN91135.1|\n",
      "      |    ||\n",
      "      |    ,| gi|407380183|gb|AFU11407.1|\n",
      "      |    ||\n",
      "      |    || gi|302171760|gb|ADK97781.1|\n",
      "      |    |\n",
      "      |    |__ gi|225423252|gb|ACN91132.1|\n",
      "      |    |\n",
      "      |    | , gi|407380005|gb|AFU11320.1|\n",
      "      |    | |\n",
      "      |    |_| gi|407380157|gb|AFU11396.1|\n",
      "      |    | |\n",
      "      |    | | gi|407380057|gb|AFU11346.1|\n",
      "      |    |\n",
      "      |    | , gi|302171782|gb|ADK97792.1|\n",
      "      |    | |\n",
      "      |    | | gi|407380151|gb|AFU11393.1|\n",
      "      |    | |\n",
      "    __|    |,| gi|407380113|gb|AFU11374.1|\n",
      "   |  |   ,|||\n",
      "   |  |   |||| gi|407380085|gb|AFU11360.1|\n",
      "   |  |   |||\n",
      "   |  |   |||, gi|407380139|gb|AFU11387.1|\n",
      "   |  |   ||||\n",
      "   |  |   |||| gi|407380181|gb|AFU11406.1|\n",
      "   |  |   |||\n",
      "   |  |   ||| gi|407380035|gb|AFU11335.1|\n",
      "   |  |   |||\n",
      "   |  |   |||_ gi|407380123|gb|AFU11379.1|\n",
      "   |  |   |||\n",
      "   |  |   ||| gi|407380187|gb|AFU11409.1|\n",
      "   |  |   ||\n",
      "   |  |   ||, gi|225423250|gb|ACN91131.1|\n",
      "   |  |   |||\n",
      "   |  |   |,| gi|407380176|gb|AFU11404.1|\n",
      "   |  |   |||\n",
      "   |  |   ||| gi|407380103|gb|AFU11369.1|\n",
      "   |  |   ||\n",
      "   |  |   || gi|407379993|gb|AFU11314.1|\n",
      "   |  |   |\n",
      "   |  |   |  , gi|225423248|gb|ACN91130.1|\n",
      "   |  |   |  |\n",
      "   |  |   |  | gi|225423296|gb|ACN91154.1|\n",
      "   |  |   |  |\n",
      "   |  |   |  | gi|225423298|gb|ACN91155.1|\n",
      "   |  |   |  |\n",
      "   |  |   | ,| gi|302171786|gb|ADK97794.1|\n",
      "   |  |   | ||\n",
      "   |  |   |,|| gi|302171788|gb|ADK97795.1|\n",
      "   |  |   |||\n",
      "   |  |   ||| gi|407380051|gb|AFU11343.1|\n",
      "   |  |   ||\n",
      "   |  |   || , gi|225423280|gb|ACN91146.1|\n",
      "   |  |   || |\n",
      "   |  |   ||,| gi|302171758|gb|ADK97780.1|\n",
      "   |  |   ||||\n",
      "   |  |   |||| gi|407380185|gb|AFU11408.1|\n",
      "   |  |   | |\n",
      "   |  |   | |, gi|407380007|gb|AFU11321.1|\n",
      "   |  |   | ||\n",
      "   |  |   |  | gi|407380105|gb|AFU11370.1|\n",
      "   |  |   |\n",
      "   |  |   |_ gi|407380133|gb|AFU11384.1|\n",
      "   |  |   |\n",
      "  ,|  |   |  , gi|225423276|gb|ACN91144.1|\n",
      "  ||  |   |  |\n",
      "  ||  |   |  | gi|407380001|gb|AFU11318.1|\n",
      "  ||  |   |  |\n",
      "  ||  |   |  | gi|302171752|gb|ADK97777.1|\n",
      "  ||  |   |  |\n",
      "  ||  |   |  | gi|313105489|gb|ADR32104.1|\n",
      "  ||  |   |  |\n",
      "  ||  |___|  | gi|407380003|gb|AFU11319.1|\n",
      "  ||      |  |\n",
      "  ||      |  , gi|225423300|gb|ACN91156.1|\n",
      "  ||      |  |\n",
      "  ||      |  | gi|302171790|gb|ADK97796.1|\n",
      "  ||      |  |\n",
      "  ||      | ,| gi|407380031|gb|AFU11333.1|\n",
      "  ||      | ||\n",
      "  ||      | ||, gi|407380077|gb|AFU11356.1|\n",
      "  ||      | |,|\n",
      "  ||      | ||| gi|407380079|gb|AFU11357.1|\n",
      "  ||      | ||\n",
      "  ||      | || gi|407380015|gb|AFU11325.1|\n",
      "  ||      | |\n",
      "  ||      | |, gi|302171764|gb|ADK97783.1|\n",
      "  ||      |,||\n",
      "  ||      |||| gi|407380171|gb|AFU11402.1|\n",
      "  ||      ||,|\n",
      "  ||      |||, gi|407380033|gb|AFU11334.1|\n",
      "  ||      ||||\n",
      "  ||      |||| gi|407380083|gb|AFU11359.1|\n",
      "  ||      |||\n",
      "  ||      |||_ gi|407380013|gb|AFU11324.1|\n",
      "  ||      |||\n",
      "  ||      ||| , gi|407380037|gb|AFU11336.1|\n",
      "  ||      |||,|\n",
      " ,||       |||| gi|407380039|gb|AFU11337.1|\n",
      " |||       |,|\n",
      " |||       ||, gi|407380173|gb|AFU11403.1|\n",
      " |||       |||\n",
      " |||       ||| gi|407380210|gb|AFU11420.1|\n",
      " |||       ||\n",
      " |||       ||_ gi|407380075|gb|AFU11355.1|\n",
      " |||       ||\n",
      " |||       || gi|407380189|gb|AFU11410.1|\n",
      " |||       |\n",
      " |||       |_ gi|407380143|gb|AFU11389.1|\n",
      " |||\n",
      " |||__ gi|302171734|gb|ADK97768.1|\n",
      " |||\n",
      " |||___ gi|302171736|gb|ADK97769.1|\n",
      " ||\n",
      " || , gi|225423290|gb|ACN91151.1|\n",
      " || |\n",
      " || | gi|407380025|gb|AFU11330.1|\n",
      " || |\n",
      " || | gi|302171774|gb|ADK97788.1|\n",
      " || |\n",
      " ||,| gi|225423244|gb|ACN91128.1|\n",
      " ||||\n",
      " ||||, gi|407380155|gb|AFU11395.1|\n",
      " |,|||\n",
      " ||| | gi|407380179|gb|AFU11405.1|\n",
      " |||\n",
      " ||| gi|225423272|gb|ACN91142.1|\n",
      " ||\n",
      " || , gi|407380061|gb|AFU11348.1|\n",
      " ||,|\n",
      " |||| gi|407380205|gb|AFU11418.1|\n",
      " |||\n",
      " |||, gi|407380069|gb|AFU11352.1|\n",
      " ||||\n",
      " || | gi|407380195|gb|AFU11413.1|\n",
      " ||\n",
      " ||_ gi|407380019|gb|AFU11327.1|\n",
      " ||\n",
      " ||_ gi|407380053|gb|AFU11344.1|\n",
      " |\n",
      " | , gi|225423284|gb|ACN91148.1|\n",
      " | |\n",
      " |_| gi|407380109|gb|AFU11372.1|\n",
      " | |\n",
      " | | gi|302171750|gb|ADK97776.1|\n",
      " |\n",
      " | , gi|302171784|gb|ADK97793.1|\n",
      " | |\n",
      " | | gi|407380089|gb|AFU11362.1|\n",
      " | |\n",
      " |,| gi|225423254|gb|ACN91133.1|\n",
      " |||\n",
      " ,|| gi|225423294|gb|ACN91153.1|\n",
      " ||\n",
      " || gi|407379991|gb|AFU11313.1|\n",
      " |\n",
      " |, gi|225423260|gb|ACN91136.1|\n",
      " ||\n",
      " || gi|407380131|gb|AFU11383.1|\n",
      " ||\n",
      " ||, gi|407380027|gb|AFU11331.1|\n",
      " |||\n",
      " ||| gi|407380029|gb|AFU11332.1|\n",
      " |||\n",
      " |,| gi|302171778|gb|ADK97790.1|\n",
      " |||\n",
      " ||| gi|225423266|gb|ACN91139.1|\n",
      " ||\n",
      " ||, gi|225423292|gb|ACN91152.1|\n",
      " |||\n",
      " ||| gi|302171776|gb|ADK97789.1|\n",
      " ||\n",
      " |, gi|407380055|gb|AFU11345.1|\n",
      " ||\n",
      " || gi|407380214|gb|AFU11422.1|\n",
      " ||\n",
      " ||, gi|407380041|gb|AFU11338.1|\n",
      " |||\n",
      " ||| gi|407380149|gb|AFU11392.1|\n",
      " |||\n",
      " ||| gi|407380169|gb|AFU11401.1|\n",
      " |||\n",
      " ,|| gi|225423268|gb|ACN91140.1|\n",
      " ||\n",
      " ||, gi|302171770|gb|ADK97786.1|\n",
      " |,|\n",
      " ||| gi|407380203|gb|AFU11417.1|\n",
      " ||\n",
      " ||, gi|407379997|gb|AFU11316.1|\n",
      " |||\n",
      " ||| gi|407380009|gb|AFU11322.1|\n",
      " |||\n",
      " ||| gi|407380141|gb|AFU11388.1|\n",
      " |||\n",
      " ||| gi|407380011|gb|AFU11323.1|\n",
      " ||\n",
      " |, gi|407380021|gb|AFU11328.1|\n",
      " ||\n",
      " || gi|407380191|gb|AFU11411.1|\n",
      " ||\n",
      " || gi|407379989|gb|AFU11312.1|\n",
      " |\n",
      " |_ gi|407380095|gb|AFU11365.1|\n",
      " |\n",
      " |  , gi|225423270|gb|ACN91141.1|\n",
      " | ,|\n",
      " |,|| gi|407380193|gb|AFU11412.1|\n",
      " |||\n",
      " ||| gi|407380147|gb|AFU11391.1|\n",
      " ||\n",
      " ||, gi|225423288|gb|ACN91150.1|\n",
      " |||\n",
      " ||| gi|302171768|gb|ADK97785.1|\n",
      " |||\n",
      " ||, gi|407380043|gb|AFU11339.1|\n",
      " |,|\n",
      " ||| gi|407380111|gb|AFU11373.1|\n",
      " |||\n",
      " ||| gi|407380212|gb|AFU11421.1|\n",
      " ||\n",
      " || gi|407380067|gb|AFU11351.1|\n",
      " ||\n",
      " || gi|302171756|gb|ADK97779.1|\n",
      " ||\n",
      " ||, gi|407380063|gb|AFU11349.1|\n",
      " |,|\n",
      " ||| gi|407380145|gb|AFU11390.1|\n",
      " ||\n",
      " || gi|407380160|gb|AFU11397.1|\n",
      " |\n",
      " |, gi|302171746|gb|ADK97774.1|\n",
      " ||\n",
      " || gi|407380137|gb|AFU11386.1|\n",
      " |\n",
      " |, gi|225423286|gb|ACN91149.1|\n",
      " ||\n",
      " || gi|302171766|gb|ADK97784.1|\n",
      " ||\n",
      " || gi|225423256|gb|ACN91134.1|\n",
      " ||\n",
      " || gi|407380164|gb|AFU11399.1|\n",
      " ||\n",
      " || gi|407380199|gb|AFU11415.1|\n",
      " ||\n",
      " |, gi|225423282|gb|ACN91147.1|\n",
      " ||\n",
      " || gi|302171748|gb|ADK97775.1|\n",
      " ||\n",
      " ,| gi|407379995|gb|AFU11315.1|\n",
      " ||\n",
      " || gi|407379987|gb|AFU11311.1|\n",
      " ||\n",
      " || gi|407380065|gb|AFU11350.1|\n",
      " |\n",
      " |, gi|302171772|gb|ADK97787.1|\n",
      " ||\n",
      " || gi|407380127|gb|AFU11381.1|\n",
      " ,|\n",
      " |, gi|407380099|gb|AFU11367.1|\n",
      " ||\n",
      " || gi|407380129|gb|AFU11382.1|\n",
      " |\n",
      " |, gi|407380119|gb|AFU11377.1|\n",
      " ||\n",
      " || gi|407380121|gb|AFU11378.1|\n",
      " ||\n",
      " || gi|407380081|gb|AFU11358.1|\n",
      " |\n",
      " , gi|302171780|gb|ADK97791.1|\n",
      " |\n",
      " | gi|407380073|gb|AFU11354.1|\n",
      " |\n",
      " , gi|407380107|gb|AFU11371.1|\n",
      " |\n",
      " | gi|407380153|gb|AFU11394.1|\n",
      " |\n",
      " , gi|407380115|gb|AFU11375.1|\n",
      " |\n",
      " | gi|407380201|gb|AFU11416.1|\n",
      " |\n",
      " |    ___ model1_F.pdb\n",
      "_|  _|\n",
      " |,| | gi|407380166|gb|AFU11400.1|\n",
      " |||\n",
      " ||| gi|407380162|gb|AFU11398.1|\n",
      " ||\n",
      " || gi|407379985|gb|AFU11310.1|\n",
      " ||\n",
      " ,| gi|407380059|gb|AFU11347.1|\n",
      " ||\n",
      " || gi|164609123|gb|ABY62783.1|\n",
      " |\n",
      " | gi|225423262|gb|ACN91137.1|\n",
      " |\n",
      " | gi|407380049|gb|AFU11342.1|\n",
      " |\n",
      " | gi|407380208|gb|AFU11419.1|\n",
      " |\n",
      " , gi|407380071|gb|AFU11353.1|\n",
      " |\n",
      " | gi|407380091|gb|AFU11363.1|\n",
      " |\n",
      " |, gi|225423274|gb|ACN91143.1|\n",
      " ||\n",
      " || gi|225423278|gb|ACN91145.1|\n",
      " ||\n",
      " || gi|302171742|gb|ADK97772.1|\n",
      " ||\n",
      " ,| gi|302171744|gb|ADK97773.1|\n",
      " ||\n",
      " || gi|313105486|gb|ADR32102.1|\n",
      " |\n",
      " | gi|225423264|gb|ACN91138.1|\n",
      " |\n",
      " , gi|407379999|gb|AFU11317.1|\n",
      " |\n",
      " | gi|407380087|gb|AFU11361.1|\n",
      " |\n",
      " | gi|407380125|gb|AFU11380.1|\n",
      "\n"
     ]
    }
   ],
   "source": [
    "Phylo.draw_ascii(tree)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "source": [
    "# Displaying trees\n",
    "\n",
    "Phylo can draw trees using matplot lib (e.g., can use savefig etc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "Phylo.draw(tree)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Phylo.draw(tree,label_func=lambda x: None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "source": [
    "# Motifs\n",
    "\n",
    "*Sequence motifs are short, recurring patterns in DNA that are presumed to have a biological function. Often they indicate sequence-specific binding sites for proteins such as nucleases and transcription factors (TF).* --The Internet\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "source": [
    "# Motif logos\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from Bio import motifs  #lower case for some reason\n",
    "m = motifs.create([\"TACAA\",\"CATGC\",\"TACTA\",\"CCCAA\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'A': [0, 3, 0, 2, 3],\n",
       " 'C': [2, 1, 3, 0, 1],\n",
       " 'G': [0, 0, 0, 1, 0],\n",
       " 'T': [2, 0, 1, 1, 0]}"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m.counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Seq('CACAA')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m.consensus"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "source": [
    "# Motif Logos\n",
    "\n",
    "Biopython uses [weblogo](http://weblogo.berkeley.edu/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "m.weblogo('logo.png',alphabet='alphabet_dna',stack_width='large')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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6arSJk3bWXmXZWZ7bZo7k+yDEXhjyMOQYA4AZaDdW4HioP8/z0ehXIyE02t/v9+lWoGCt7XQ6Wus7TwCBvw30VHeed+z7StM98V2+WZN2Sl3kuc2yN3WfSG2kPIiix1H0uO4TgUZAu7EaNzE1yzJjDC3ri+O4/CN6cDQaFT17pZTWmn6FMYbAD/bKnn5/at6Z6l96Uybt8txm2dn8Cvl2ogGAOD7m/EHd5wK1QbuxMjcxtdPp0Er+24zH46LHv7OzU/4RAj90TTe3eV2v3vAdukpdpOkrhPx5nO/2+0/Q+28ttBsrcxNTkyTRWt82Zx+GYRRFxbd0i0BTAAyBv/XS12nyU83rZZo5aWfMZa/3Y40hPwgO6Qsh9m7rWxvzztor+rqWU5XyoN9/gmQAbYN2Yx3e5/hvU+T3ReBvM3WhOv/q1H0WTZy0S5KXafqqspejnfScPwiCwzXz61FmQKXeUn7AalYgxvFxv/+kgheCJkC7sabaYup84J+ZAihD4N9K9sqefHdS8cKc2zRn0s6Yy27XVBAvaa98EBx67S7TTYDW0zy3XncbBsHhcCgw67/10G6sz0HgpxF+ys5L6/XmzY//b2iPn3oz5UfWH94sBlSJEHtCPFzzmBuh87yj3i5aGlKxJkzaKXXR7Rq3afNnSHlAW+Oq/5hpPaWNiJ7+QCkPRqNniP3bDe3G+hzE1CRJ0jSlxfxpenOq5PlXaWDgp6BeFCIrJi+rzHA+Q8oDasWKSVbKcL4FNwf+ymmso95Juyw76/V+9Hf8KDqKose1b4W39ipNX2XZmY/wHwSHo9Ez54eFhkC74YTLXP0bpKhcQtHdeWkyVxaP9xYVz6jqCaU6r+zc1uGwnEZ8HNsrm73JnBytxnTcXqN+FB3F8XFDbhY5f9DvP4nj417vxzx3PGCr1Ns0fR3Hf3R7WGgCtBuu+OpMF4P/t6myx0+hndKYU42ydY7WcFT3jP5PC7XqPqNZ5tKcfn/qZIpOHsjx12O323lrmbTzF/WF2BsMnjb2jtDHH8757mTypwZ+8mEdaDccchz4jTFpmmbZh9soIUQYhv3+DfMfvgP/NpUtWYcQe0FwSDcBTejwOSynwXf5+JuxeCgYY3qqT78/Xf+YpP9FP/5jfPfzHFHqotP5l48jR9FRv/+k4SHQR+zv979Ap3+boN1wy2XgN8acnp5aO3tHFkXRYDBY+bD3CvxKXSj11vf64Q3VhITnvRc9V8Nrg6eD6PGn/BBu9/WOvxnLfXn389Zm7dXJyXc+ZpoGg6ebktzG+d5FKQ/G468dHhDqhXbDLZeBn1b5SSnjOA6CwFqbZRkt9ytn7rv3KS4R+GmzkKflQjNowR3FTppl//j4/n27VsZcFjcotDugmjUHdWU8dVhOIzqKBl/O3k06XO4r9sT4m3EFk3bdrnE+z802KuqT09Mf3O5gnEy+bcIQF6wP7YZzLgM/Je4dDoflcnx0N1DO1X9fiwM/7Q7ylzKsmDIPgsOK19IrdUErEjzNVnC+G0WPKwv/Dstp3HZ1ud3gG/JwKIZODnUbT4P8mzjQrfU0SV46PGC//6T2/QuwPrQbPrhc1S+lnM/YTyP/nLu/A8qyszR95SkifkxsUue8eBA8KtZkGXOZ59ZtJVZr36fpqzy3w6Hw3UTaK9t70XN1aQ3F8MZ7av6AD74cdE3XyavkNk9fp14n7Xws6AtDvnFRnzEm5T624cEMtBueOEvgwxiz1vZ6PcZYv9+nJf1KKRr8H4/Hq5/iXI/fXw7zIDgMQ97kMVIfJVs43x2Pv/F6i+OwnMad6TLc7vT1N2mX57bbdVxYrIJ/SoDKoN3wxFkCn8XPWedVZgJ/lp0lyUvnU+BBcLhBY4Np+jpJfnJ4wCg6Ggy+dHjAMofLZ5bcM3P6w6mTBcDM56Sdj9l9pKyHrYF2w58NC/yedv0OBl+GYUP/hW6T55YyDLriKWA43DCzfEkMh/OCzNuk3c6Omyam7Pz8fzd88x7AMtBueNWgNPi3KQK/j6FRJPf2yu2qmaEYhjy8+3mMMacrgZmHHbo+lvWFIR8OF2XNAtgIaDd8+03dJ7Asa696vRduj8n5Lsp5edU1XVdXb3wcL3/1Msaix9G9nr9Y8lOipy476D5WqEh54PyYANVDu+HbxgR+H3v0+/0nWAblT/IycbU7Vh7I+PjeN86DpwOx56wH3DVde+VsSt7HbpRNWaECsADajQpsTOD30UPauHn9DeKwnAbf5YMvByssk+EP+ODp6ikjZ5h3xuEY4ExxZycam5AfYEloN6qxMYHfuaLQLThnLk3vhbPPenwcr7wxJngUrHDLfxvaoevqaABQhnajMu0N/Ejm74/DKbqQh2uujuk/6QeHzkplN3bSDmDTod2ozMYEfiH2nB/TmEvnx4Tei56rvbB8182Y2+DpgO86m9Zp5qQdwEZDu1GljQn8Pubj3RYEA8ZYdpa5KqLFbk+xeV/ioZivzLGyZk7aAWwutBsV25jAHwSPnMf+LHuTZWduj9lmeqqTl84KXMbHcfDI2VBbyMPoKLr7ectZf9LOxwp8pS6cHxPAN7Qb1dukBD7WXnU6z93W7mQbWMCUKHXhdqeDlPvr3FrZK9t53nE1WCcP5Pjr1es73MjtGbL10nH7yEG5iUX5oOXQbtRikwI/8xb7w5APBk83aJG/1tNO57nbxAaj0Vfr7AdzWE6D7/LxN2Px0H0SOod5QNl66biNuTw5+W9XZ0KQuQ82DtqNWmzMUD/h/MF4/HUcH7s9bJ7bk5PvkuTlRiz3S9PXzqN+FB2tE/XT16mrq5cx1n/S93H1Msbkvux/sahC172sM2knxEPn61Xz3G7EBxiAoN2oy4b1+AtKXSTJS+ddf8ZYGHIqztu0AQBrr7LsLMveON+IuGZJN7e3w9FR5HBBzY0cdjLYGum4k+Sl8+WlXqssAjiEdqPGNP6bGvhJlp2l6StPO/KD4FDKffp/jTcBSl1oPVXqrY/chesXI3ZbTmNDrTZp52O0nzE2mXy7iYmorb1yW22SIZVhg6HdYLVO9m924CdKXeS5zbI3/s5BiD0h9qTcpy+E2PPRtlLbZ+17raf0tY8hDRIEh3F8vH7L2HnecZVYe3PJAzl6Nlph0s5Hpz8IDkejZ26PWQHnqx2F2JtM/uTwgOAQ2g22Rruxvm0I/MTaqzy3Sr3N8+ruIoPgkL5YLQFw0cWheO/yzG4hxF4Y8ig6cnLjkrxMXCXW3nSrjTRae3Vy8p3zf/pNHPDvdJ67HdPaxDehJdBuFCqYobjR9gT+grVXSr2l3W7Iy0towiIMucPt47nNu6br6mhbYPB0ED2+95bfPLfdrnF+Mmuu26iYj82Nw6FAFa4GQrsxY7V2Y01bGPjLjLnU+hetpzRN7vbEmozzXSn3/a1RMJfm9PvTlk/RzeC7fPRstMKkXa/3wsdE1aZ0eX3sTcU4fzOh3Zi3cruxji0P/DO0nhrzjv5P9wRODtsEQXBI0w30he/lXac/nDrMaLE1Vpu085SdgjEWBIeDwdMmr/XzEfUZuvtNhXbjRtVP9rcr8M8z5tKYd/Qf+zjp3tixAVpXyD4mfJVyn/Pd6pcu9170HCbW3jIrT/Z7iv2c78bxcTMz+qXp6zR9hSUOLYF2Y4GKJ/vbHvgXKO8vKt8KWHs1v3RghXuFYmFggfMH5aQuFNfpcR+p3VeTnWW1Z59ouNUm7fzFfsaYEHtxfNyc1NTGXPZ6P/q4w5byYDR61rQkHIB2405VTvYj8MM96KnuPO9gim6xlSftrL3qdo2/ASch9qLoKIoe15uXwt/mW0T9ZkK7sYwqJ/s3IKbu7Oy8m0zeZBgj8usoih6KRQkvnRer2GLrTNr52Nw/o/r0lFpP89zmufW30aaxUd9cGn9D3HyXhzz0lKrWCbQby6tssn8zAv/b0ehfnU7dJ7LlvhqNHgWLylm6naILeTgUQ1dHW5/zVGLrTNopddHtmgpSO0h5EASPpNyX8sD5GkBKOmnMuzy3vv+WBtbZMpcmt3lu8wpiXnAYhDwMeVhv6Zcbod24l2om+xH44YPFgT99nSY/OauZzXf55E+TpjVSzncYrzNpZ+1Vmr7y3fWfEQSHxUKTYg3K4u2glGWSMUYZJ9nHvTOVpdBo2urFKuP9PAr/IQ+rf+kbod1YQQWT/Qj88MGCwO+2nAZjbPTVKHi0aHShLm5ziq0/aaf1NEleNnabSe3CkPf7XzRhv6K9shTvm5CJlsb/g0dBvXcAaDdWU8Fk/4aV5YXq2Svr9n42Po6befUyxuLjWB44u97se9t70bNXqw8DSrk/Gj0bjb6a3wPSckFwOBp9NRyKeqO+vbLZWdY13c//7+e9H3vrRH2+y6OjaPzNeCiG0dFaHT773mZvsq7pnnx3krxM9LSGsQe0Gytbv924E3r88MFtPX635TSCw2D0bOTqaD44X4HsatJOqYsse1NlKYpmomITtVfey84y9VY5qdN64/g8DSFkZ5mTKQOxJ6KjqMplgGg31uR1sn8zAn9DTvJCKX/3H3eurauF8yGsBk7RzXM7McmcTtoZc0nhv211KDjfjaLHrupLrSy3ubpQuc3Xb+LlgYweR3euyKNNAbnNzTsHNR3kgQx5GD2OvF6GaDec8DfZ35SYugACf13Uher8y+XfOxTD5iw7Wqxruk46c8THpF2eW9oTX01dx7pwvhuGPAge1ZuC12G8F3si5GF0FN23862nOjvLnJwDYyzkIe0FcB5Q0W64Opq/yf6mxNQFEPhr4bycRnwc95/0XR3NN+e7dPzt0KVClEpdbFPtCaofTSUlazwNh7GWFtzRmrs1D0WrCJ0EGOfLANFubES70ZSYugACfy3cltOQB3L89djV0arhvOPie4euMZdKvaValJt4EyDlQVFSst7xfD3VFFmdjK5T39r5mK3bRQB0BxA9jtbsX6Ld2Ih2oykxdQEE/uo5n6IbfzNucnKx27h9H1iF6bip0oRSb5tciPJjJck9KfdrX6zHXMd7Ig+k78lpqjLm6mg0ExHycIU7ALQbpPntRlNi6gII/BVzXk5jg6bo5rntwdRSe5tQph1KCVBxFUqK7pQaiPNdKfcrqBy9vHpT7jQWLQNcfiMA2o2yhrcbTYmpCyDwV2mzNqVUwPmcZfW1txejytSMsZl0e0VpymWUq0dSaKevm9CPv43zeB8c1n/9FuyVdfh33ZkPGO3GjIa3G02JqQsg8LdZEZacWJx9FtrA7dQ487k8fk00c5GdZa7Cj6fFCj6g3VisKTF1AQT+TUfzzfR1eXh5pk9ZY2Lambx45f5r8SOHo9NeP0hADoPg2ehTyheK965S7rD7j4TXiPYiuqqUU1k+YLQb/jQlpi6AwL8RaApZ66m17629otvtrUwyL+UB5w9mitnca0wbgb8CFPidx/t11r7Vy3k1ASdvBdqNWk6mKTF1AQT+BqKKq1SQrcpSbE1Gc9tS7tMXCy5pBP4KzPT4oQnQbsxbvt1wqCkxdQEE/iaoYI84rf1mpRGz8kja+tdDeeSwqCHLfC5xL6rdz2ShubJ2qhuxgNzf5/koinhY55LsB5zvy/U65T9r9p/S7Ph/LPv5ln+12x6fMTXsF2f77n7laOmm4/c3vSef8dnHH7tpi9BurOC2dsOhpsTUBRD4a6T1lJKEOb83p2wtnD/4uJm7/mkwWhBEe9+VunCYCpfyzPf7T1wd0BW9s+PpyMdx/KTf1IRrFNGLQP4fy6Yf4/GbNYbBy9F3X7DPbmq150Ps+s5uOefy7YiTv4vOfF+wfbH4zgDthhP+2o2mxNQFEPhrkWVnafrK7XVb5F0PgsPmr5LNsrM8tw7v6KU8GI2eNeoPb0Xgnxp2ptjUsJ81+1mzy/WWuD/k7HHwIfhRdHceyP1ZMGixgt/L+ZsbtBsb0W7sOjwWbAetp92ucXvpCrEXx8dR9NjhMX2LosebdcJwgx8S9v/c5VB7GrFv69hc/n+auiLkvz6tokC7QTai3UDgh1/RetrpPHdb8C2KjgaDLx0eEGBZJzH7jH/o668/v/5jxqaG/V5+6O7f1OX1wsegwpli/+Os9492Y7Mg8MOv9Hov3F69Quzh6oXafMbZSfzpW5oOp/9PzYe1e/ca/3+jZufLH5ZG+5dZIrfC7MDXt0+aTM2nBQoLHi/WMfzHOoz3BbQbmwWBH37FeXF3WnAL0AgUiW9bmDYzBT6zaK68BrCsfCswc0/gcJZhBf9rbkCCbjjoz6dBi8KZWmcMAO3GZkHgh18JQ56mrxwekDbzlHNaATTUZ/xX9wSOtrQxdnu/fB1u1xWu98ei3dgsCPzwK7R1xO013Ok8j+PjOP6jw2NWRqkLtwdsct2aLdOcfAl+WMbc5OBbx54QD4VAuzGj4e0GAj/M6vefBMFhmr5ytSPF2vdJ8lOWvYmiozDkTdh6uwxjLpPkpzx3Vl+LMRbHxwj8lZlqjQyJvhX7NtFukI1oN+rZIm+tzbLMWiuEiKI7aj1hH39djLnMsjfOs3AIsUfJNyrLT3kvlFVU61/cXrpBcNjAqN+Kffx1Q7vhBNoNh2qIqVrrTqdj7Yd3R0o5Go04v3VXDAJ/7bSeKnWh9S9u81IRyrhJk3nl7Ju+M3UUhTupg/KxWIjjrKJSHoQhb2x/BYG/Amg30G7cl+92o4ah/m63a62NoigIgjRNtdZJkgwGdaTFgOVQDQn6mtJuG/POVZkNOshtw4NUuGL+fJY8srVX5Ud8XKIzqDGi3sn2lfEGWB7ajeVV3G5UHfiVUsYYznkR6bvdbp7nCPybonwxE7qdp5IVzu9/rX0/f203pGon1dmkd4MuWixCBrgR2o1CE9qNGgI/Y0x+rJoVBAFjzFprrV0w2g9NRvNP84Wk6GJmpeutfCvdkIvwRuXuQlE/m32s+lVctACwMrQbNap5VX8R7LXWQVNnqmA1pSqZd6xMKRe+LD34fv7B9RXTgWWNuiYB2gztRgUatJ1vx9s6I1ceBYFsxjLDLcP5gxsvcn/lqIHg81wBtBueoN1Y2W/qPoFPrm9X96lBQ2mt9VyGFqUUzSiBJ7RSp+6z2HLWWrzPFdBaK6WKXWYtUXWPf2Yiv7ypr+IzgY2mte52u9Qs0lrRMAzpR51OhzGG+0UnjDFpmhYLco0xxV7cIAj6/T6u3PVZa+fvX2m7UxRF9MHGTOj66C2VUvb7fcZYnudJkhS3VlEU9fv9tiw1W9DP9mE8HtPrnp+fX19f02J+IUTFpwEb7fz8fP76HI/H9NNaPthb6fz8XIhPdVyklDNvu5Sy7nPcBqPRiN2l7nPcBvQ+B0FwfX09mUzm3+QwDOs+x4pUPdQvpaSm5PT0NEmSJEno7a74NDxRSu3cpe5z3AZ5nltrpZSTyeT6+pru38tZocCJPM+NMVLKOI7jONZaUwaO6+vr8XjMOb9xqgWg+bIsY4wFQUBtCCWRow983adWhRrm+IfDoRCChhCpHelvS4YvIQRGPitAF2e/36ebyDiO+/2+tbbb7dZ9aluF3md6e/v9PmXXplE6KSV9i5ut9QkhOOec8ziOiz4ZdU+LR+o+x+0UxzG1IUEQ0Oe5JYG/hlX91FGj5Vec822KlEKI0Wh0enpqjMH0pz804JzneTHxSf3RPM8R+53TWtOYXBiG5aF+9PVdEUJMJpM0TdM0pWxmmNH3jeJ9+ba1XbewdcwvbDkawBiNRnWfyNYq5ueEEEWXaGZCut4z3A7F+xwEQbGE4vr6ejwe000t55wW64AT4/GYQn4YhsPhkJV6/LC+8lqK4gNMPyrutFryeW7Qdr6tgY6+b0IIGnA2xhT9Ts75cDjEm++QEILuYmf2OxWr0Fu0CroSVLFsMBgopTB25ZyUcjAYxHFchPniU00j0IPBoCWf56YUvgO4Lwo/87NFeZ5rrbdm4Ujt6O6qWJZLj+R5HoZheYgFHCoKlwdBgGF/f+iDzRhLkqRVbzUCPwAAQItgqB8AAKBF6szVP5+vqjxs27axFwAAgHsxxlBOAiHEzL6bBTG0zsCf53mv1ys/EgQBLbxUSqVpihlEAACAG6VpSknwim9HoxHFzcUxtM45/iRJ0jQt348UWZQ7nU6xchsAAADKjDEnJyeMsTiOpZRpmmqtoyiiuLk4htbZ46dx/vk81UopRH0AAIDb0BZEqpXFPpYqpcyDd8bQmuf4pZRZltG5RlFE4xJUB6zGEwMAAGgymhmfSTxA394ZQ+sc6p+vWDMcDremYA8AAIBvSqk8z7MsowRQy+Qgqm07H43zU7a10WhEM/3ldQoAAACwmFKKFvYbY5YsMtSUBD7FOoUiDTgAAAAso9frZVlG5TPufHJTEvgUuw7aVSIJAADg/owxSqkiFw5N6ltradHfYrUF/iRJdnZ2Op0OfVucK7r7AAAAi+V53ul0ilw4xR3AMvlvahvqV0pR1I+iiHNOFSmKPYgAAABwm2J+PAgC2h9HVZ3md8jPq3OOP8uycua+MAzbUxURAABgHVmWJUlSzI9T3eFlRs1rXtxXpOsXQiBBLwAAwPKKGDpfoHyBpqzqBwAAgAo0ZVU/AAAAVACBHwAAoEUQ+AEAAFoEgR8AAKBFEPgBAABaBIEfAADgE6p5U3xdJMVb7Qj3fcJqr8juU+UOgR8AANqFIqsxhrLfaK0p9T39lB5XSllry88pnqA/Kr6dyZBfPgL7mFeffSygV5TRK3bhz796+ZHyC5Vf4sbzKU54QaU+BH4AAGiXNE0ZY71eL8/zPM///ve/J0lijOl2u/SEmW+p4D09Qr9SZJ0v/6j8EsURlFLF15Svtoj69CvlJ9Dv/vOf/yw/Qsc3xuR5Tk8o/wqdQFGwpxgwWDCosOvwrQQAAGg+KaXWWgihlBJC/Pvf//7222+NMUWXOo5jIYQx5ueff2aM5Xk+HA7ZxzBP+fApDJd/VH6J4gh/+9vfioMLIeI4DoJAKdXtdqWUUsput0vPLF79H//4x5///OfikSAI8jy31oZhSE/Isqz4FWstnc8ydfkIAj8AALRLEARJkoRhqJQyxnzxxRdSSs55USymSID/29/+tnjktlIyN/6oOMIf/vCH4uDluvPD4ZB6/5Rtt/zqv/vd78qPhGFIXf8iKW/5V4p4P1PUfkGNewR+AABoFymlMSYIAhp1py51OXhnWUbf7u3tMcaiKOr1ekKIch+dnln+EU20R1FUPsJf//rXmYMTznm/30+SJIqimSf85S9/UUqVH+GcMuxIRwAAAHdJREFU0yvSS4RhWPxKFEXFmAFjTAhBI/8L/nzk6gcAgLaj9XTlOjda6/K3xRMoJAshkiShOvLzvztzhNuesODVZx7p9Xo0d3DjE4qQTz+iUYQFpW4R+AEAAJaltabefBiGyxfEW0eWZdbaOI5dHRCBHwAAoEX+P3ro6liUR35FAAAAAElFTkSuQmCC",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image(filename='./logo.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "source": [
    "# Reading Motifs\n",
    "\n",
    "Biopython supports a number of motif formats: JASPAR, MEME, TRANSFAC\n",
    "\n",
    "These formats are associated with databases (JASPAR, TRANSFAC) and tools (MEME).\n",
    "\n",
    "Of particular interest are sequence motifs for transcription factor binding.\n",
    "\n",
    "[JASPAR](http://jaspar.genereg.net/)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Reading Motifs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "f = open('../files/MA0004.1.sites') # unlike other parts of Biopython, can't just provide filename to open\n",
    "arnt = motifs.read(f,'sites') #JASPAR sites"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Bio.motifs.jaspar.Motif at 0x119703d00>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arnt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Seq('CACGTG')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arnt.consensus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        0      1      2      3      4      5\n",
      "A:   4.00  19.00   0.00   0.00   0.00   0.00\n",
      "C:  16.00   0.00  20.00   0.00   0.00   0.00\n",
      "G:   0.00   1.00   0.00  20.00   0.00  20.00\n",
      "T:   0.00   0.00   0.00   0.00  20.00   0.00\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(arnt.counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('AACGTG'),\n",
       " Seq('AACGTG'),\n",
       " Seq('AACGTG'),\n",
       " Seq('AACGTG'),\n",
       " Seq('CGCGTG')]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arnt.instances"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Scoring Matrices\n",
    "\n",
    "The counts attribute can be normalized to represent probabilities at each position"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        0      1      2      3      4      5\n",
      "A:   0.20   0.95   0.00   0.00   0.00   0.00\n",
      "C:   0.80   0.00   1.00   0.00   0.00   0.00\n",
      "G:   0.00   0.05   0.00   1.00   0.00   1.00\n",
      "T:   0.00   0.00   0.00   0.00   1.00   0.00\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(arnt.counts.normalize())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A *pseudocount* is often added at each position to prevent probability from going to zero."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        0      1      2      3      4      5\n",
      "A:   0.21   0.85   0.03   0.03   0.03   0.03\n",
      "C:   0.72   0.03   0.90   0.03   0.03   0.03\n",
      "G:   0.03   0.08   0.03   0.90   0.03   0.90\n",
      "T:   0.03   0.03   0.03   0.03   0.90   0.03\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(arnt.counts.normalize(pseudocounts=0.8))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "source": [
    "# PSSM\n",
    "\n",
    "The *position-specific scoring matrix* is the position weight matrix (with pseudocounts) expressed as a log (base 2) odds ratios"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        0      1      2      3      4      5\n",
      "A:  -0.27   1.77  -2.86  -2.86  -2.86  -2.86\n",
      "C:   1.53  -2.86   1.84  -2.86  -2.86  -2.86\n",
      "G:  -2.86  -1.69  -2.86   1.84  -2.86   1.84\n",
      "T:  -2.86  -2.86  -2.86  -2.86   1.84  -2.86\n",
      "\n"
     ]
    }
   ],
   "source": [
    "pwm = arnt.counts.normalize(pseudocounts=0.8)\n",
    "pssm = pwm.log_odds()\n",
    "print(pssm)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A negative value means a nucleotide is less likely than the background at a specific position.\n",
    "\n",
    "By default a uniform background is assumed, but this can be changed with the `background` parameter of `log_odds`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div id=\"logpssm\" style=\"width: 500px\"></div>\n",
       "<script>\n",
       "$('head').append('<link rel=\"stylesheet\" href=\"https://bits.csb.pitt.edu/asker.js/themes/asker.default.css\" />');\n",
       "\n",
       "    var divid = '#logpssm';\n",
       "\tjQuery(divid).asker({\n",
       "\t    id: divid,\n",
       "\t    question: \"What is the PSSM score for A at a position if it occurs 5 times out of 20 sequences (no pseudocount)?\",\n",
       "\t\tanswers: [\"-1\",\"-.25\",\"0\",\".25\",\"1\",\"None of the above\"],\n",
       "        server: \"https://bits.csb.pitt.edu/asker.js/example/asker.cgi\",\n",
       "\t\tcharter: chartmaker})\n",
       "    \n",
       "$(\".jp-InputArea .o:contains(html)\").closest('.jp-InputArea').hide();\n",
       "\n",
       "\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%html\n",
    "<div id=\"logpssm\" style=\"width: 500px\"></div>\n",
    "<script>\n",
    "$('head').append('<link rel=\"stylesheet\" href=\"https://bits.csb.pitt.edu/asker.js/themes/asker.default.css\" />');\n",
    "\n",
    "    var divid = '#logpssm';\n",
    "\tjQuery(divid).asker({\n",
    "\t    id: divid,\n",
    "\t    question: \"What is the PSSM score for A at a position if it occurs 5 times out of 20 sequences (no pseudocount)?\",\n",
    "\t\tanswers: [\"-1\",\"-.25\",\"0\",\".25\",\"1\",\"None of the above\"],\n",
    "        server: \"https://bits.csb.pitt.edu/asker.js/example/asker.cgi\",\n",
    "\t\tcharter: chartmaker})\n",
    "    \n",
    "$(\".jp-InputArea .o:contains(html)\").closest('.jp-InputArea').hide();\n",
    "\n",
    "\n",
    "</script>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Search for Motifs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "from Bio import SeqIO\n",
    "from Bio.Seq import Seq\n",
    "largeseq = SeqIO.read('../files/bnip3.fasta','fasta') #load with same alphabet as motif\n",
    "smallseq = Seq('AAACCCACGTGACTATATA')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can search for exact matches"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5 CACGTG\n"
     ]
    }
   ],
   "source": [
    "for pos,seq in arnt.instances.search(smallseq):\n",
    "    print(\"%i %s\" % (pos,seq))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3452 CACGTG\n",
      "4058 CACGTG\n",
      "6181 AACGTG\n",
      "8591 CGCGTG\n",
      "10719 CACGTG\n",
      "10998 CACGTG\n"
     ]
    }
   ],
   "source": [
    "for pos,seq in arnt.instances.search(largeseq.seq): # pass sequence, not seqrecord\n",
    "    print(\"%i %s\" % (pos,seq))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Searching for Motifs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results = [(pos,str(seq)) for pos,seq in arnt.instances.search(largeseq.seq)]\n",
    "len(results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[(3452, 'CACGTG'), (4058, 'CACGTG'), (6181, 'AACGTG'), (8591, 'CGCGTG'), (10719, 'CACGTG'), (10998, 'CACGTG')]\n"
     ]
    }
   ],
   "source": [
    "print(results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('CACGTG'),\n",
       " Seq('AACGTG'),\n",
       " Seq('AACGTG'),\n",
       " Seq('AACGTG'),\n",
       " Seq('AACGTG'),\n",
       " Seq('CGCGTG')]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arnt.instances"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Searching for Motifs\n",
    "\n",
    "We can use the PSSM to get a fuzzier match"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1065"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pwm = arnt.counts.normalize(pseudocounts=0.8)\n",
    "pssm = pwm.log_odds()\n",
    "positions = [pos for pos,seq in pssm.search(largeseq.seq)]\n",
    "len(positions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "167"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results = [(pos,score) for pos,score in pssm.search(largeseq.seq, threshold=4)]\n",
    "len(results)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The score is a $log_2$ likelihood so a score of 4 is $2^4=16$ times more likely to occur as part of the motif than as part of the (uniform) background"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(508, 5.975107)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Searching for Motifs\n",
    "\n",
    "Positions may be negative if the motif was found on the reverse strand."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(508, 5.975107), (-13823, 6.0461903)]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results[:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "pos = results[1][0] #-13823\n",
    "hit = largeseq.seq[pos:pos+len(arnt)]  #negative indices can still be used to retrieve matched subsequence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-13823 508\n",
      "CACGGG CCCGTG\n"
     ]
    }
   ],
   "source": [
    "print(pos,len(largeseq)+pos)\n",
    "print(hit, hit.reverse_complement())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        0      1      2      3      4      5\n",
      "A:   4.00  19.00   0.00   0.00   0.00   0.00\n",
      "C:  16.00   0.00  20.00   0.00   0.00   0.00\n",
      "G:   0.00   1.00   0.00  20.00   0.00  20.00\n",
      "T:   0.00   0.00   0.00   0.00  20.00   0.00\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(arnt.counts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Some more marine biology\n",
    "\n",
    "<img src=\"https://c2.staticflickr.com/4/3285/3293134375_635141a7b3_b.jpg\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Your Herculean Task\n",
    "\n",
    "&nbsp;&nbsp;0\\. Get input files of 179 hydra sequences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "!wget https://MSCBIO2025.github.io/files/hydra179.aln\n",
    "!wget https://MSCBIO2025.github.io/files/hydra179.dnd\n",
    "!wget https://MSCBIO2025.github.io/files/hydra179.fasta"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "source": [
    " 2. Display the phylogenetic tree from the clustal alignment (hydra179.dnd)\n",
    " 3. Identify the subsequence of length 20 that has the most variation amount these sequences (like last time)\n",
    " 4. Use clustal to compute the multiple alignment of these 179 length 20 subsequences\n",
    " 5. Display the phylogenetic tree from this alignment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "#!/usr/local/bin/python\n",
    "from Bio import SeqIO\n",
    "from Bio import AlignIO\n",
    "from Bio.Seq import Seq\n",
    "from Bio import Phylo\n",
    "from Bio.Align.Applications import ClustalwCommandline\n",
    "import sys\n",
    "\n",
    "sys.argv = ['fake','../files/hydra179.aln']\n",
    "a = AlignIO.read(sys.argv[1],'clustal')\n",
    "\n",
    "#the following is perhaps not the most readable, but it counts\n",
    "#the number of unique sequences of length 20 at each position in align\n",
    "cnts = [len({str(s.seq) for s in a[:,i:i+20]}) for i in range(len(a[0])-20)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "maxpos = cnts.index(max(cnts))\n",
    "maxseqs = a[:,maxpos:maxpos+20]\n",
    "\n",
    "# have to write out to a file to compute msa with clustal\n",
    "out = open('subalign.fasta','w')\n",
    "SeqIO.write(maxseqs, out, 'fasta')\n",
    "out.close() # must close before reading \n",
    "\n",
    "cline = ClustalwCommandline(\"clustalw\", infile=\"subalign.fasta\", outfile='subalign.aln')\n",
    "# cline()\n",
    "\n",
    "# msa of the subsequences\n",
    "maxalign = AlignIO.read('subalign.aln','clustal')\n",
    "\n",
    "tree = Phylo.read('subalign.dnd','newick')\n",
    "tree.root.branch_length = 0 #prettier\n",
    "Phylo.draw(tree,label_func=lambda x: None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "celltoolbar": "Slideshow",
  "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": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}