viraq_kaiju_presentation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "os.chdir(os.path.expanduser(\"~\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/home/jovyan'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pwd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import HTML\n",
    "import random\n",
    "\n",
    "def hide_toggle(for_next=False):\n",
    "    this_cell = \"\"\"$('div.cell.code_cell.rendered.selected')\"\"\"\n",
    "    next_cell = this_cell + '.next()'\n",
    "\n",
    "    toggle_text = 'Toggle show/hide'  # text shown on toggle link\n",
    "    target_cell = this_cell  # target cell to control with toggle\n",
    "    js_hide_current = ''  # bit of JS to permanently hide code in current cell (only when toggling next cell)\n",
    "\n",
    "    if for_next:\n",
    "        target_cell = next_cell\n",
    "        toggle_text += ' next cell'\n",
    "        js_hide_current = this_cell + '.find(\"div.input\").hide();'\n",
    "\n",
    "    js_f_name = 'code_toggle_{}'.format(str(random.randint(1,2**64)))\n",
    "\n",
    "    html = \"\"\"\n",
    "        <script>\n",
    "            function {f_name}() {{\n",
    "                {cell_selector}.find('div.input').toggle();\n",
    "            }}\n",
    "\n",
    "            {js_hide_current}\n",
    "        </script>\n",
    "\n",
    "        <a href=\"javascript:{f_name}()\">{toggle_text}</a>\n",
    "    \"\"\".format(\n",
    "        f_name=js_f_name,\n",
    "        cell_selector=target_cell,\n",
    "        js_hide_current=js_hide_current, \n",
    "        toggle_text=toggle_text\n",
    "    )\n",
    "\n",
    "    return HTML(html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Viraq"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "### -Viraq is one of 4  internal \"Havets Helse\" projects\n",
    "### -lead by Søren Grove and Craig Morton\n",
    "### -Tomasz Furmanek and Me will in dialog with Søren and Craig be Leading a workpackage for bioinformatic analysis and infrastructure"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "### -Analysis of viral composition in water samples as well as in diseased fish\n",
    "### -Analysis of Viral subtype evolution and distribution\n",
    "### -will be utilizing long read nanopore and pacbio sequencing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"1600\"\n",
       "            height=\"800\"\n",
       "            src=\"2019-10-15.png\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x7fa458f98b70>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import IFrame\n",
    "IFrame(src='2019-10-15.png', width=1600, height=800)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"1200\"\n",
       "            height=\"800\"\n",
       "            src=\"https://www.youtube.com/embed/RcP85JHLmnI\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.YouTubeVideo at 0x7fa458f98cc0>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hide_toggle(for_next=True)\n",
    "from IPython.lib.display import YouTubeVideo\n",
    "YouTubeVideo('RcP85JHLmnI',width=1200, height=800)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] No such file or directory: 'viraq/nanopore_seq.svg'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-10-fcf4399e54c1>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mIPython\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcore\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdisplay\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mSVG\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mSVG\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'viraq/nanopore_seq.svg'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/srv/conda/envs/notebook/lib/python3.7/site-packages/IPython/core/display.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, data, url, filename, metadata)\u001b[0m\n\u001b[1;32m    618\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmetadata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    619\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 620\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    621\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_check_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    622\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/srv/conda/envs/notebook/lib/python3.7/site-packages/IPython/core/display.py\u001b[0m in \u001b[0;36mreload\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    643\u001b[0m         \u001b[0;34m\"\"\"Reload the raw data from file or URL.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    644\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfilename\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 645\u001b[0;31m             \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfilename\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_read_flags\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    646\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    647\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0murl\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'viraq/nanopore_seq.svg'"
     ]
    }
   ],
   "source": [
    "from IPython.core.display import SVG\n",
    "SVG(filename='viraq/nanopore_seq.svg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] No such file or directory: 'viraq/metagenomics_viraq.svg'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-11-73b67160ea0e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mIPython\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcore\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdisplay\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mSVG\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mSVG\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'viraq/metagenomics_viraq.svg'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/srv/conda/envs/notebook/lib/python3.7/site-packages/IPython/core/display.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, data, url, filename, metadata)\u001b[0m\n\u001b[1;32m    618\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmetadata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    619\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 620\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    621\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_check_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    622\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/srv/conda/envs/notebook/lib/python3.7/site-packages/IPython/core/display.py\u001b[0m in \u001b[0;36mreload\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    643\u001b[0m         \u001b[0;34m\"\"\"Reload the raw data from file or URL.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    644\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfilename\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 645\u001b[0;31m             \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfilename\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_read_flags\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    646\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    647\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0murl\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'viraq/metagenomics_viraq.svg'"
     ]
    }
   ],
   "source": [
    "from IPython.core.display import SVG\n",
    "SVG(filename='viraq/metagenomics_viraq.svg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"1600\"\n",
       "            height=\"800\"\n",
       "            src=\"kaio74_viraq_ scripts for metagenomic analysis of long reads.html\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x7fa4588ceac8>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import IFrame\n",
    "IFrame(src='kaio74_viraq_ scripts for metagenomic analysis of long reads.html', width=1600, height=800)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# subsampling and QC check"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "DyQXO6uJEaiM",
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "2019-10-16T19:30:49 prefetch.2.8.2: 1) Downloading 'SRR7946391'...\n",
      "2019-10-16T19:30:49 prefetch.2.8.2:  Downloading via https...\n",
      "2019-10-16T19:30:52 prefetch.2.8.2: 1) 'SRR7946391' was downloaded successfully\n",
      "2019-10-16T19:30:52 prefetch.2.8.2: 'SRR7946391' has 0 unresolved dependencies\n",
      "Read 85711 spots for SRR7946391\n",
      "Written 85711 spots for SRR7946391\n"
     ]
    }
   ],
   "source": [
    "!cd ~\n",
    "!mkdir -p viraq/QC\n",
    "!mkdir -p viraq/kaiju_results\n",
    "\n",
    "# define name of SRA file\n",
    "SRAname='SRR7946391'\n",
    "#Get file from SRA accession\n",
    "!prefetch $SRAname\n",
    "\n",
    "#input file directory\n",
    "SRAfiles='ncbi/public/sra'\n",
    "#quality check path\n",
    "QC1_sub='viraq/QC/'+SRAname+'_sub'\n",
    "\n",
    "#convert to fastq\n",
    "os.chdir(SRAfiles)\n",
    "!fastq-dump $SRAname\n",
    "\n",
    "#subsampling\n",
    "fastqfile=SRAfiles+'/'+SRAname +'.fastq'\n",
    "os.chdir(os.path.expanduser(\"~\"))\n",
    "subsample=SRAfiles+'/'+SRAname+'_sub.fq.gz'\n",
    "!seqtk sample $fastqfile 5000 | gzip > $subsample\n",
    "!nanoQC -o $QC1_sub $subsample"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"1200\"\n",
       "            height=\"800\"\n",
       "            src=\"viraq/QC/SRR7946391_sub/nanoQC.html\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x7fa4584772b0>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import IFrame\n",
    "IFrame(src='viraq/QC/SRR7946391_sub/nanoQC.html', width=1200, height=800)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "H_DxsPE1Eail",
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# taxonomic assignment using Kaiju"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "S8VUe4a6Eai8",
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "19:42:25 Reading database\n",
      " Reading taxonomic tree from file kaiju/db/nodes.dmp\n",
      " Reading index from file kaiju/db/viruses/kaiju_db_viruses.fmi\n",
      "Output file: viraq/kaiju_results/SRR7946391_sub_viralref\n",
      "19:42:26 Start classification using 8 threads.\n",
      "19:42:52 Finished.\n",
      "Writing viraq/kaiju_results/SRR7946391_Krona_sub_viralref.html...\n"
     ]
    }
   ],
   "source": [
    "#can test with smaller virus database to run faster\n",
    "kaijudb2='kaiju_db_viruses.fmi'\n",
    "kaijudbpath2='kaiju/db/viruses'+'/'+kaijudb2\n",
    "\n",
    "kaijuresults_sub2= 'viraq/kaiju_results/'+SRAname+'_sub_viralref'\n",
    "kronaresults_sub2= 'viraq/kaiju_results/'+SRAname+'_Krona_sub_viralref'\n",
    "kronasub2html='viraq/kaiju_results/'+SRAname+'_Krona_sub_viralref.html'\n",
    "\n",
    "!kaiju -t kaiju/db/nodes.dmp -f $kaijudbpath2 -i $subsample -z 8 -a greedy -e 5 -v -o $kaijuresults_sub2\n",
    "!kaiju2krona -t kaiju/db/nodes.dmp -n kaiju/db/names.dmp -i $kaijuresults_sub2 -o $kronaresults_sub2\n",
    "!ktImportText -o $kronasub2html $kronaresults_sub2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"1400\"\n",
       "            height=\"800\"\n",
       "            src=\"viraq/kaiju_results/SRR7946391_Krona_sub_viralref.html\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x7fa45846b0f0>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "IFrame(src='viraq/kaiju_results/SRR7946391_Krona_sub_viralref.html', width=1400, height=800)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Further tasks to be completed:\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "## -Setting up and running the  Nanopore sequencing minion cells on our own samples: scedueled delivery of the minion chips are 28.10.2019\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "## -Preparing scripts for 1) binning reads according to taxonomic assignment and 2.) assembly and polishing of viral genomes."
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Slideshow",
  "colab": {
   "name": "viraq_kaiju.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}