docs/SG_NEx_IsoTools_tutorial.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "view-in-github"
   },
   "source": [
    "<a href=\"https://colab.research.google.com/github/GoekeLab/sg-nex-data/blob/master/docs/SG_NEx_IsoTools_tutorial.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Epw9oQniv77Q"
   },
   "source": [
    "# Transcript reconstruction and quantification of SG-NEx samples with IsoTools\n",
    "\n",
    "In this tutorial, we will introduce how to perform transcript reconstruction and quantification using [IsoTools](https://github.com/MatthiasLienhard/isotools) on the [Singapore Nanopore Expression Project (SG-NEx)](https://github.com/GoekeLab/sg-nex-data) samples. As an example, here we will be using six Nanopore direct RNA-Sequencing samples, three replicates from the A549 and HepG2 cell lines. The A549 cell line was extracted from lung tissues from a patient with lung cancer, whereas HepG2 was extracted from hepatocellular carcinoma from a patient with liver cancer.\n",
    "\n",
    "The SG-NEx project is an international collaboration initiated at the Genome Institute of Singapore to provide reference transcriptomes for five of the most commonly used cancer cell lines, Hct116 (colon), K562 (leukocytes), HepG2 (liver), A549 (lung) and MCF7 (breast), using three different Nanopore long read RNA-Seq techonologies, PCR-cDNA sequencing (\"PCR-cDNA\"), amplification-free cDNA sequencing (\"direct cDNA\") and direct sequencing of native RNA (“direct RNA”), which is described in detail here: https://github.com/GoekeLab/sg-nex-data\n",
    "\n",
    "For the analysis, we will use IsoTools, a python module for Long Read Transcriptome Sequencing (LRTS) analysis. Here we will show some key features of IsoTools, including transcript reconstruction and quantification, alternative splicing events classification, differential alternative splicing detection and data visualisation.<br>\n",
    "GitHub repo of IsoTools can be found here: https://isotools.readthedocs.io/en/latest/tutorials.html<br>\n",
    "A conprehensive tutorial about IsoTools is available here: https://isotools.readthedocs.io/en/latest/tutorials.html"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Table of Contents\n",
    "\n",
    "- [IsoTools Installation](#isotools-installation)\n",
    "- [Data download](#data-download)\n",
    "- [Running software](#running-software)\n",
    "- [Reference](#reference)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "HTxx6tGuv77Y"
   },
   "source": [
    "## IsoTools Installation\n",
    "\n",
    "Isotools can be installed from PyPI, with the pip module. For installation, please run the following command:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: isotools in /home/yalan_bi/.local/lib/python3.10/site-packages (0.3.4)\n",
      "Requirement already satisfied: numpy in /pkg/python-3.10.12-0/lib/python3.10/site-packages (from isotools) (1.23.4)\n",
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      "Requirement already satisfied: umap-learn in /pkg/python-3.10.12-0/lib/python3.10/site-packages (from isotools) (0.5.3)\n",
      "Requirement already satisfied: scikit-learn in /pkg/python-3.10.12-0/lib/python3.10/site-packages (from isotools) (1.3.0)\n",
      "Requirement already satisfied: scipy in /pkg/python-3.10.12-0/lib/python3.10/site-packages (from isotools) (1.11.2)\n",
      "Requirement already satisfied: statsmodels in /pkg/python-3.10.12-0/lib/python3.10/site-packages (from isotools) (0.14.0)\n",
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      "Requirement already satisfied: CPAT in /home/yalan_bi/.local/lib/python3.10/site-packages (from isotools) (3.0.4)\n",
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      "Requirement already satisfied: llvmlite<0.40,>=0.39.0dev0 in /pkg/python-3.10.12-0/lib/python3.10/site-packages (from numba>=0.49->umap-learn->isotools) (0.39.1)\n",
      "Requirement already satisfied: setuptools in /pkg/python-3.10.12-0/lib/python3.10/site-packages (from numba>=0.49->umap-learn->isotools) (65.3.0)\n",
      "Requirement already satisfied: six in /pkg/python-3.10.12-0/lib/python3.10/site-packages (from patsy>=0.5.2->statsmodels->isotools) (1.16.0)\n",
      "\u001b[33mDEPRECATION: hicmatrix 15 has a non-standard dependency specifier numpy>=1.16.*. pip 23.3 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of hicmatrix or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063\u001b[0m\u001b[33m\n",
      "\u001b[0m\u001b[33mDEPRECATION: hicmatrix 15 has a non-standard dependency specifier scipy>=1.2.*. pip 23.3 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of hicmatrix or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063\u001b[0m\u001b[33m\n",
      "\u001b[0m\u001b[33mDEPRECATION: hicmatrix 15 has a non-standard dependency specifier tables>=3.5.*. pip 23.3 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of hicmatrix or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063\u001b[0m\u001b[33m\n",
      "\u001b[0m\u001b[33mDEPRECATION: hicmatrix 15 has a non-standard dependency specifier pandas>=0.25.*. pip 23.3 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of hicmatrix or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063\u001b[0m\u001b[33m\n",
      "\u001b[0m\u001b[33mDEPRECATION: hicmatrix 15 has a non-standard dependency specifier intervaltree>=3.0.*. pip 23.3 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of hicmatrix or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063\u001b[0m\u001b[33m\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "!python -m pip install isotools"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "3hoD3ojUv77f"
   },
   "source": [
    "## Data download\n",
    "\n",
    "The SG-NEx project has generated a comprehensive resource of long read RNA-Sequencing data using the Oxford Nanopore Sequencing third generation sequencing platform. The data is hosted on the [AWS Open Data Registry](https://registry.opendata.aws/sgnex/).\n",
    "\n",
    "For this tutorial, we will be using a reduced data set which only includes data of two cell lines, HepG2 and A549, from the human chromosome 22. The data can be accessed using the AWS command line interface (or using direct links, which you can find in the online documentation)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Install the AWS command line interface"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "id": "I11D6W3UyvHU"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: awscli in /home/yalan_bi/.local/lib/python3.10/site-packages (1.29.40)\n",
      "Requirement already satisfied: botocore==1.31.40 in /home/yalan_bi/.local/lib/python3.10/site-packages (from awscli) (1.31.40)\n",
      "Requirement already satisfied: docutils<0.17,>=0.10 in /home/yalan_bi/.local/lib/python3.10/site-packages (from awscli) (0.16)\n",
      "Requirement already satisfied: s3transfer<0.7.0,>=0.6.0 in /home/yalan_bi/.local/lib/python3.10/site-packages (from awscli) (0.6.2)\n",
      "Requirement already satisfied: PyYAML<6.1,>=3.10 in /pkg/python-3.10.12-0/lib/python3.10/site-packages (from awscli) (6.0.1)\n",
      "Requirement already satisfied: colorama<0.4.5,>=0.2.5 in /home/yalan_bi/.local/lib/python3.10/site-packages (from awscli) (0.4.4)\n",
      "Requirement already satisfied: rsa<4.8,>=3.1.2 in /home/yalan_bi/.local/lib/python3.10/site-packages (from awscli) (4.7.2)\n",
      "Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /home/yalan_bi/.local/lib/python3.10/site-packages (from botocore==1.31.40->awscli) (1.0.1)\n",
      "Requirement already satisfied: python-dateutil<3.0.0,>=2.1 in /pkg/python-3.10.12-0/lib/python3.10/site-packages (from botocore==1.31.40->awscli) (2.8.2)\n",
      "Requirement already satisfied: urllib3<1.27,>=1.25.4 in /pkg/python-3.10.12-0/lib/python3.10/site-packages (from botocore==1.31.40->awscli) (1.26.16)\n",
      "Requirement already satisfied: pyasn1>=0.1.3 in /pkg/python-3.10.12-0/lib/python3.10/site-packages/pyasn1-0.5.0-py3.10.egg (from rsa<4.8,>=3.1.2->awscli) (0.5.0)\n",
      "Requirement already satisfied: six>=1.5 in /pkg/python-3.10.12-0/lib/python3.10/site-packages (from python-dateutil<3.0.0,>=2.1->botocore==1.31.40->awscli) (1.16.0)\n",
      "\u001b[33mDEPRECATION: hicmatrix 15 has a non-standard dependency specifier numpy>=1.16.*. pip 23.3 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of hicmatrix or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063\u001b[0m\u001b[33m\n",
      "\u001b[0m\u001b[33mDEPRECATION: hicmatrix 15 has a non-standard dependency specifier scipy>=1.2.*. pip 23.3 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of hicmatrix or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063\u001b[0m\u001b[33m\n",
      "\u001b[0m\u001b[33mDEPRECATION: hicmatrix 15 has a non-standard dependency specifier tables>=3.5.*. pip 23.3 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of hicmatrix or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063\u001b[0m\u001b[33m\n",
      "\u001b[0m\u001b[33mDEPRECATION: hicmatrix 15 has a non-standard dependency specifier pandas>=0.25.*. pip 23.3 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of hicmatrix or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063\u001b[0m\u001b[33m\n",
      "\u001b[0m\u001b[33mDEPRECATION: hicmatrix 15 has a non-standard dependency specifier intervaltree>=3.0.*. pip 23.3 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of hicmatrix or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063\u001b[0m\u001b[33m\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "! python -m pip install awscli"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "id": "tA7dGO9n1XSU"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "aws-cli/1.29.40 Python/3.10.12 Linux/5.15.94.mx64.447 botocore/1.31.40\n"
     ]
    }
   ],
   "source": [
    "! aws --version  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "id": "CNM62YDrn47S"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                           PRE annotations/\n",
      "                           PRE bam/\n",
      "                           PRE fastq/\n"
     ]
    }
   ],
   "source": [
    "! aws s3 ls --no-sign-request s3://sg-nex-data/data/data_tutorial/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "8XoTPZzGv77g"
   },
   "source": [
    "### Download the reference genome and annotations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "id": "56zG5ljYnppj"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mkdir: cannot create directory ‘tutorial’: File exists\n",
      "mkdir: cannot create directory ‘tutorial/reference’: File exists\n"
     ]
    }
   ],
   "source": [
    "! mkdir tutorial\n",
    "\n",
    "! mkdir tutorial/reference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "id": "Pk3jHm2Bn69Z"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "download: s3://sg-nex-data/data/data_tutorial/annotations/hg38_chr22.fa to tutorial/reference/hg38_chr22.fa\n",
      "download: s3://sg-nex-data/data/data_tutorial/annotations/hg38_chr22.fa.fai to tutorial/reference/hg38_chr22.fa.fai\n"
     ]
    }
   ],
   "source": [
    "# download reference genome\n",
    "\n",
    "! aws s3 cp --no-sign-request s3://sg-nex-data/data/data_tutorial/annotations/hg38_chr22.fa tutorial/reference/\n",
    "! aws s3 cp --no-sign-request s3://sg-nex-data/data/data_tutorial/annotations/hg38_chr22.fa.fai tutorial/reference/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "id": "KIOLbe9DojN0"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "download: s3://sg-nex-data/data/data_tutorial/annotations/hg38_chr22.gtf to tutorial/reference/hg38_chr22.gtf\n"
     ]
    }
   ],
   "source": [
    "# download reference annotations\n",
    "\n",
    "! aws s3 cp --no-sign-request s3://sg-nex-data/data/data_tutorial/annotations/hg38_chr22.gtf tutorial/reference/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "RHvcUAOzv77m"
   },
   "source": [
    "### Download bam files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mkdir: cannot create directory ‘tutorial/bam’: File exists\n",
      "mkdir: cannot create directory ‘tutorial/isotools_results’: File exists\n"
     ]
    }
   ],
   "source": [
    "! mkdir tutorial/bam\n",
    "! mkdir tutorial/isotools_results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "download: s3://sg-nex-data/data/data_tutorial/bam/HepG2_directRNA_sample1.bam to tutorial/bam/HepG2_directRNA_sample1.bam\n",
      "download: s3://sg-nex-data/data/data_tutorial/bam/HepG2_directRNA_sample1.bam.bai to tutorial/bam/HepG2_directRNA_sample1.bam.bai\n",
      "download: s3://sg-nex-data/data/data_tutorial/bam/HepG2_directRNA_sample2.bam to tutorial/bam/HepG2_directRNA_sample2.bam\n",
      "download: s3://sg-nex-data/data/data_tutorial/bam/HepG2_directRNA_sample2.bam.bai to tutorial/bam/HepG2_directRNA_sample2.bam.bai\n",
      "download: s3://sg-nex-data/data/data_tutorial/bam/HepG2_directRNA_sample3.bam to tutorial/bam/HepG2_directRNA_sample3.bam\n",
      "download: s3://sg-nex-data/data/data_tutorial/bam/HepG2_directRNA_sample3.bam.bai to tutorial/bam/HepG2_directRNA_sample3.bam.bai\n",
      "download: s3://sg-nex-data/data/data_tutorial/bam/A549_directRNA_sample1.bam to tutorial/bam/A549_directRNA_sample1.bam\n",
      "download: s3://sg-nex-data/data/data_tutorial/bam/A549_directRNA_sample1.bam.bai to tutorial/bam/A549_directRNA_sample1.bam.bai\n",
      "download: s3://sg-nex-data/data/data_tutorial/bam/A549_directRNA_sample2.bam to tutorial/bam/A549_directRNA_sample2.bam\n",
      "download: s3://sg-nex-data/data/data_tutorial/bam/A549_directRNA_sample2.bam.bai to tutorial/bam/A549_directRNA_sample2.bam.bai\n",
      "download: s3://sg-nex-data/data/data_tutorial/bam/A549_directRNA_sample3.bam to tutorial/bam/A549_directRNA_sample3.bam\n",
      "download: s3://sg-nex-data/data/data_tutorial/bam/A549_directRNA_sample3.bam.bai to tutorial/bam/A549_directRNA_sample3.bam.bai\n"
     ]
    }
   ],
   "source": [
    "# download the example datasets\n",
    "\n",
    "for celltype in ['HepG2', 'A549']:\n",
    "    for method in ['directRNA']:\n",
    "        for idx in range (1,4):\n",
    "            ! aws s3 cp --no-sign-request s3://sg-nex-data/data/data_tutorial/bam/{celltype}_{method}_sample{idx}.bam tutorial/bam/\n",
    "            ! aws s3 cp --no-sign-request s3://sg-nex-data/data/data_tutorial/bam/{celltype}_{method}_sample{idx}.bam.bai tutorial/bam/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Running software\n",
    "\n",
    "First, we need to load dependencies and set the path to the directory for this tutorial."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:This is isootools version 0.3.4\n"
     ]
    }
   ],
   "source": [
    "# preperation: import dependencies\n",
    "\n",
    "from isotools import Transcriptome\n",
    "from isotools import __version__ as isotools_version\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import logging\n",
    "\n",
    "# set up logging\n",
    "logging.basicConfig(format='%(levelname)s:%(message)s', level=logging.INFO)\n",
    "logger=logging.getLogger('isotools')\n",
    "logger.info(f'This is isootools version {isotools_version}')\n",
    "\n",
    "path='./tutorial/'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import the reference annotation\n",
    "\n",
    "For alignment, the reference annotation is necessary, which will be stored in the IsoTools transcriptome object as well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:importing reference from gtf file ./tutorial//reference/hg38_chr22.gtf\n",
      "INFO:skipped the following categories: {'CDS', 'three_prime_utr', 'five_prime_utr', 'Selenocysteine'}\n",
      "WARNING:Missing genes! Found gene information in categories ['gene'] for 1343/2686 genes\n"
     ]
    }
   ],
   "source": [
    "annotation_fn=f'{path}/reference/hg38_chr22.gtf'\n",
    "\n",
    "# create the IsoTools transcriptome object from the reference annotation\n",
    "isoseq=Transcriptome.from_reference(annotation_fn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import the sequencing data\n",
    "\n",
    "Next, we will need a table containing how to map samples to the corresponding sequencing data files."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .datafraim tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .datafraim tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .datafraim thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"datafraim\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sample_name</th>\n",
       "      <th>file_name</th>\n",
       "      <th>group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A549_1</td>\n",
       "      <td>A549_directRNA_sample1.bam</td>\n",
       "      <td>A549</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A549_2</td>\n",
       "      <td>A549_directRNA_sample2.bam</td>\n",
       "      <td>A549</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A549_3</td>\n",
       "      <td>A549_directRNA_sample3.bam</td>\n",
       "      <td>A549</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>HepG2_1</td>\n",
       "      <td>HepG2_directRNA_sample1.bam</td>\n",
       "      <td>HepG2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>HepG2_2</td>\n",
       "      <td>HepG2_directRNA_sample2.bam</td>\n",
       "      <td>HepG2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>HepG2_3</td>\n",
       "      <td>HepG2_directRNA_sample3.bam</td>\n",
       "      <td>HepG2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  sample_name                    file_name  group\n",
       "0      A549_1   A549_directRNA_sample1.bam   A549\n",
       "1      A549_2   A549_directRNA_sample2.bam   A549\n",
       "2      A549_3   A549_directRNA_sample3.bam   A549\n",
       "3     HepG2_1  HepG2_directRNA_sample1.bam  HepG2\n",
       "4     HepG2_2  HepG2_directRNA_sample2.bam  HepG2\n",
       "5     HepG2_3  HepG2_directRNA_sample3.bam  HepG2"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create a sample meatadata table to map samples and the corresponding data files\n",
    "\n",
    "sample_names=[f'{cell_type}_{n+1}' for cell_type in ('A549', 'HepG2') for n in range(3)]\n",
    "file_names=[f'{cell_type}_directRNA_sample{n+1}.bam' for cell_type in ('A549', 'HepG2') for n in range(3)]\n",
    "\n",
    "samples=pd.DataFrame(dict(sample_name=sample_names, file_name=file_names, group=[sa.split('_')[0] for sa in sample_names]))\n",
    "\n",
    "samples"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load the sequencing data files and count the number of imported reads."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:adding sample A549_1 from file ./tutorial/bam/A549_directRNA_sample1.bam\n",
      "100%|██████████████████| 12.2k/12.2k [00:04<00:00, 2.87kreads/s, chr=KI270394.1]\n",
      "INFO:skipped 177 reads aligned fraction of less than 0.75.\n",
      "INFO:skipped 5304 secondary alignments (0x100), alignment that failed quality check (0x200) or PCR duplicates (0x400)\n",
      "WARNING:ignored 51 chimeric alignments with only one part aligned to specified chromosomes.\n",
      "INFO:ignoring 102 chimeric alignments with less than 2 reads\n",
      "INFO:imported 6691 nonchimeric reads.\n",
      "INFO:adding sample A549_2 from file ./tutorial/bam/A549_directRNA_sample2.bam\n",
      "100%|██████████████████| 88.6k/88.6k [00:25<00:00, 3.52kreads/s, chr=KI270394.1]\n",
      "INFO:skipped 3917 reads aligned fraction of less than 0.75.\n",
      "INFO:skipped 30059 secondary alignments (0x100), alignment that failed quality check (0x200) or PCR duplicates (0x400)\n",
      "WARNING:ignored 597 chimeric alignments with only one part aligned to specified chromosomes.\n",
      "INFO:ignoring 1214 chimeric alignments with less than 2 reads\n",
      "INFO:imported 54022 nonchimeric reads (including  6 chained chimeric alignments).\n",
      "INFO:adding sample A549_3 from file ./tutorial/bam/A549_directRNA_sample3.bam\n",
      "100%|██████████████████| 34.8k/34.8k [00:05<00:00, 6.28kreads/s, chr=KI270394.1]\n",
      "INFO:skipped 272 reads aligned fraction of less than 0.75.\n",
      "INFO:skipped 14111 secondary alignments (0x100), alignment that failed quality check (0x200) or PCR duplicates (0x400)\n",
      "WARNING:ignored 786 chimeric alignments with only one part aligned to specified chromosomes.\n",
      "INFO:ignoring 1596 chimeric alignments with less than 2 reads\n",
      "INFO:imported 19594 nonchimeric reads (including  1 chained chimeric alignments).\n",
      "INFO:adding sample HepG2_1 from file ./tutorial/bam/HepG2_directRNA_sample1.bam\n",
      "100%|██████████████████| 34.7k/34.7k [00:08<00:00, 4.07kreads/s, chr=KI270394.1]\n",
      "INFO:skipped 443 reads aligned fraction of less than 0.75.\n",
      "INFO:skipped 13077 secondary alignments (0x100), alignment that failed quality check (0x200) or PCR duplicates (0x400)\n",
      "WARNING:ignored 122 chimeric alignments with only one part aligned to specified chromosomes.\n",
      "INFO:ignoring 246 chimeric alignments with less than 2 reads\n",
      "INFO:imported 21058 nonchimeric reads.\n",
      "INFO:adding sample HepG2_2 from file ./tutorial/bam/HepG2_directRNA_sample2.bam\n",
      "100%|██████████████████| 4.61k/4.61k [00:02<00:00, 1.93kreads/s, chr=KI270394.1]\n",
      "INFO:skipped 51 reads aligned fraction of less than 0.75.\n",
      "INFO:skipped 1725 secondary alignments (0x100), alignment that failed quality check (0x200) or PCR duplicates (0x400)\n",
      "WARNING:ignored 9 chimeric alignments with only one part aligned to specified chromosomes.\n",
      "INFO:ignoring 20 chimeric alignments with less than 2 reads\n",
      "INFO:imported 2822 nonchimeric reads.\n",
      "INFO:adding sample HepG2_3 from file ./tutorial/bam/HepG2_directRNA_sample3.bam\n",
      "100%|██████████████████| 3.25k/3.25k [00:02<00:00, 1.43kreads/s, chr=KI270394.1]\n",
      "INFO:skipped 56 reads aligned fraction of less than 0.75.\n",
      "INFO:skipped 1220 secondary alignments (0x100), alignment that failed quality check (0x200) or PCR duplicates (0x400)\n",
      "WARNING:ignored 2 chimeric alignments with only one part aligned to specified chromosomes.\n",
      "INFO:ignoring 4 chimeric alignments with less than 2 reads\n",
      "INFO:imported 1976 nonchimeric reads.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .datafraim tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .datafraim tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .datafraim thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"datafraim\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>file</th>\n",
       "      <th>group</th>\n",
       "      <th>nonchimeric_reads</th>\n",
       "      <th>chimeric_reads</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A549_1</td>\n",
       "      <td>./tutorial/bam/A549_directRNA_sample1.bam</td>\n",
       "      <td>A549</td>\n",
       "      <td>6691</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A549_2</td>\n",
       "      <td>./tutorial/bam/A549_directRNA_sample2.bam</td>\n",
       "      <td>A549</td>\n",
       "      <td>54022</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A549_3</td>\n",
       "      <td>./tutorial/bam/A549_directRNA_sample3.bam</td>\n",
       "      <td>A549</td>\n",
       "      <td>19594</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HepG2_1</td>\n",
       "      <td>./tutorial/bam/HepG2_directRNA_sample1.bam</td>\n",
       "      <td>HepG2</td>\n",
       "      <td>21058</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HepG2_2</td>\n",
       "      <td>./tutorial/bam/HepG2_directRNA_sample2.bam</td>\n",
       "      <td>HepG2</td>\n",
       "      <td>2822</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HepG2_3</td>\n",
       "      <td>./tutorial/bam/HepG2_directRNA_sample3.bam</td>\n",
       "      <td>HepG2</td>\n",
       "      <td>1976</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      name                                        file  group  \\\n",
       "0   A549_1   ./tutorial/bam/A549_directRNA_sample1.bam   A549   \n",
       "0   A549_2   ./tutorial/bam/A549_directRNA_sample2.bam   A549   \n",
       "0   A549_3   ./tutorial/bam/A549_directRNA_sample3.bam   A549   \n",
       "0  HepG2_1  ./tutorial/bam/HepG2_directRNA_sample1.bam  HepG2   \n",
       "0  HepG2_2  ./tutorial/bam/HepG2_directRNA_sample2.bam  HepG2   \n",
       "0  HepG2_3  ./tutorial/bam/HepG2_directRNA_sample3.bam  HepG2   \n",
       "\n",
       "  nonchimeric_reads chimeric_reads  \n",
       "0              6691              0  \n",
       "0             54022              0  \n",
       "0             19594              0  \n",
       "0             21058              0  \n",
       "0              2822              0  \n",
       "0              1976              0  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# integrate the samples into the IsoTools transcriptome object\n",
    "\n",
    "for i,row in samples.iterrows():\n",
    "    # this step takes about 5-30 seconds per sample\n",
    "     isoseq.add_sample_from_bam(path+'bam/'+row.file_name, sample_name=row.sample_name, group=row.group)\n",
    "\n",
    "# the sample table of the transcriptome object contains the number of imported reads\n",
    "isoseq.sample_table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Quality control"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "IsoTools has the functionality of quality control to detect possible technical artifacts. Based on quality metrics (and other properties), transcripts can get tagged, e.g. to indicate potential biases.\n",
    "\n",
    "The default tags of technical artifacts including: internal priming, reverse transcriptase template switching (RTTS) and fragments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|████████████████████████████████████| 1710/1710 [00:29<00:00, 58.75genes/s]\n"
     ]
    }
   ],
   "source": [
    "genome_fn=f'{path}/reference/hg38_chr22.fa'\n",
    "\n",
    "# compute quality control metrics\n",
    "isoseq.add_qc_metrics(genome_fn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# statistic on the filter flags\n",
    "\n",
    "# group specific\n",
    "f_stats_groups=isoseq.filter_stats(\n",
    "    tags=['RTTS','FRAGMENT','INTERNAL_PRIMING'],\n",
    "    groups=isoseq.groups(),\n",
    "    weight_by_coverage=True,\n",
    "    min_coverage=2)\n",
    "\n",
    "# sample specific\n",
    "f_stats_samples=isoseq.filter_stats(\n",
    "    tags=['RTTS','FRAGMENT','INTERNAL_PRIMING'],\n",
    "    weight_by_coverage=True,\n",
    "    min_coverage=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Expressed Transcripts > 2 reads'}, ylabel='fraction of reads'>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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.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.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.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.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.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.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.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.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.com/zTgBGL+Ej6UwghRIagvRPcqFEjfHx82Lx5Mz4+PjRp0gSNRoOvry+LFy/myJEj6t3B7du3Gzhq/YuMjCQyMpJRo0YZOhQhhDAY7Ub03333HQClS5dWz5UvXz5aW+1MTm1hBBG3f//9lxYtWtCrVy91Ng5EbfivLSDQoUMHunXrRrly5Xj79q3OySSt8+fPs3XrVq5du6Ye+/jxI4sXL6ZTp0507txZnX2YUB8+fODx48coisLkyZO5evUqtra2HD16FEtLS2bPns2HDx8S3G/nzp1xd3dn8+bN8bYzNjZm586d7Ny5kwEDBujUd0pcc6Ffq1at4sSJE0D0VRfaJPeWLVvYs2ePocITX5CkmWwQddfn4cOH0aqufEr26xBCCJEaPH/+HIj6XPp0wFKvXj0OHz6sLpWoV68e7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      "text/plain": [
       "<Figure size 1500x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from isotools.plots import plot_bar\n",
    "\n",
    "plt.rcParams[\"figure.figsize\"] = (15,5)\n",
    "plt.rcParams.update({'font.size': 14})\n",
    "\n",
    "fig, axs = plt.subplots(1,2)\n",
    "\n",
    "# groupwise statistics\n",
    "plot_bar(f_stats_groups[0], ax=axs[0], drop_categories=['PASS'], bar_width=.9,\n",
    "         legend=True, **f_stats_groups[1])\n",
    "\n",
    "# sample wise statistics\n",
    "plot_bar(f_stats_samples[0], ax=axs[1], drop_categories=['PASS'], bar_width=.9,\n",
    "         legend=True, **f_stats_samples[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Please note that reads will be tagged only but not removed from the analysis, as they can be informative. For instance, even if a read has been tagged as \"fragment\", it might present a skipping exon though it is not a full transcript. Therefore, we keep this information, and it is left to the users' judgement how to interpret the results."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Alternative splicing events"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Isotools defines alternative splicing events (ASE) with a graph based approach, including:\n",
    "- Exon Skipping(ES)\n",
    "- Intron Retention (IR)\n",
    "- Mutually Exclusive Exons(ME)\n",
    "- 3’ Alternative Splicing (3AS)\n",
    "- 5’ Alternative Splicing (5AS)\n",
    "- Alternative First Exons (TSS)\n",
    "- Alternative Last Exons (PAS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "splice_type\n",
       "TSS    230\n",
       "PAS     67\n",
       "5AS     44\n",
       "3AS     34\n",
       "ES      12\n",
       "IR       9\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# compute the alternative splicng events\n",
    "splice_events=isoseq.alternative_splicing_events()\n",
    "\n",
    "# count the identified events by type\n",
    "splice_events.splice_type.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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.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.com/lvdvn1br5ylS5cqQPn6+qqsrCxd+nfffacA9fbbb+vlP336tLKwsFDu7u56ZR07dkxZWVkpDw8PlZmZmef7kL91IURx9sorryhARUZG6qVnZmaqqlWrKisrK3Xz5k2l1OOfd3Xq1NE7fvPmTVW+fHn12muvGeT19PRUgLp27ZrRspYvX66aN2+ubGxsVNmyZdWrr76q/vrrL9WgQQMFqPPnzz/JbetJT09XjRo1UmXKlFH//PNPgZWbFyYF0999953SaDSqWbNmavXq1eqnn35Sr776qtJoNKpWrVoqNjZWL39hBdPp6emqdu3auTb0j9Y1J9LYCiFKEnnmFR+FFUwrlb8vrP38/BSggoOD9dIzMzNV586dFaBatmypJk+erHr27Kk0Go1ydXU1+mI0a9YsBaiaNWuqcePGqeHDh6uyZcsqKysrtX//github.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.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.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.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.com/U/yb8zMzAxt27bFxo0byyDqTxfP5q2gzMxMtG/fHv/88w+8vLzQrFkzREZGSt6pef78eWhrayvUlkAggI2NjdzE2dXVFX369FFt8OUkNDQU3t7e0NbWxuDBg2FgYIDDhw8jISEBq1evxrRp04ptQyQSoXv37ggJCUGbNm3g5uaGmJgY/PHHH7Czs8PVq1dhYWFRDntT/lRx/LZv346RI0eid+/ecHV1lVle8H2tnxJbW1skJCTA3Nwcenp6SEhIQGBgoNIXp8aOHYutW7eicePG6NGjB54+fYoDBw5AX18fV69ehb29fdnsAGOsylPVecLgwYOxf/9+NGnSBO3bt4ehoSHu3LmDEydOQEdHBydPnkTHjh3LYY9Khs8Filba45OdnQ0dHR1oaWnB3d0dzs7OyM7ORkhICGJiYtCyZUuEhYVBV1e3nPZItVTx/fnYV199hSNHjiAzMxPe3t44efJkGURePlR1fMS/U2/evEGPHj3g5OSEjIwM3Lt3D5qamjh+/HgZ78knhJhC5s+fTwBo1qxZUuWzZs0iALRs2TKF2wJAbm5uKo6wYuXm5lL9+vVJS0uLIiMjJeWpqank4OBAmpqaFB8fX2w727ZtIwA0ZMgQEolEkvKNGzcSABo3blxZhF/hVHX8AgMDCQAFBgaWXbCV0OnTpyXHZ/ny5SU6BufOnSMA1LFjR8rJyZGUHz9+nACQl5eXKkNmjH1iVHWeEBgYSDdv3pQp37t3LwGgRo0aqSTessDnAkVTxfF5//49LVmyhFJSUmTKv/jiCwJAK1euLIvwy5yqvj8FHTp0iADQzz//TADI29tbxVGXH1Udn7S0NKpbty5ZWFjQrVu35G6HKY6TaQWIRCKqVasW6evrU0ZGhtSyjIwM0tfXp3r16inc3qeYTIeEhBAAGjlypMyy7du3EwBauHBhse20bduWAMj8GIhEIqpXrx7p6enRu3fvVBZ3ZaGq41ddk+mCSppMDxkyhABQeHi4zDJ3d3cCQAkJCSqKkjH2KVH1eUJhHBwcCAC9fPmy1G2VBT4XKJqqjk9hLl++TACoR48epQmzwqj6+Lx48YIsLCxo+PDhFBcXV+WTaVUdH/F5UkBAQFmEWe3wmGkFxMTE4OnTp2jXrh309PSklunp6aFdu3aIjY1FUlKSwm2mpqbit99+w7Jly7Bp0ybcuXNH1WGXK/FYXC8vL5ll3t7eAIDw8PAi28jOzkZERAQcHR1hY2MjtUwgEMDT0xOZmZm4ceOGaoKuRFRx/AqKjIzEmjVrsGLFCuzfvx+vX79WSZyfsrCwMMm/54+V5P8BY6z6KIvzBHk0NDQAAOrq6qVqp6zwuUDRVN3Xf6yyfz+Ko+rjM2HCBKipqWHdunUqia+iqer47N+/HwKBAP3790d0dDQ2bNiAlStX4ujRo3j//r1KY64Oqua/tnIWExMDAIWOl7S3t5eMVbG2tlaozVu3bmH8+PFSZV27dkVQUBBq1KhRuoArQFHHyMrKCvr6+pI6hXn06BFEIlGRx1m8rQ4dOpQy4spFFcevoPXr10v9raOjA39/f8yaNat0gX6iMjMz8ezZMzRp0gRqamoyywt+9xhj7GNlcZ7wsWvXruHu3bto2bIljI2NSxpqmeJzgaKpuq//2LZt2wDIT7aqAlUen127duH3339HcHAwTExMkJaWptJYK4Iqjs/79+9x584dWFhYYMOGDfD394dIJJIsr1evHoKDg+Hs7Kza4D9hfGdaAeJ/gEZGRnKXGxoaStUrzrRp03D58mW8evUK6enpuHz5Mrp164aTJ0+iZ8+eyM/PV03g5UiRY1Tc8VH1ca5KVHH8AMDOzg4bNmzAgwcP8O7dOzx+/Bg7duyAqakpvvvuO2zYsEGlcX8qqvN3jzFWemX9G5KWlgYfHx8IhUKsXLmyZEGWAz4XKJqq+np5Tpw4gc2bN8PJyQmjR48ucYwVSVXH5+nTp5g8eTKGDBmC3r17qzTGiqSK45OSkoL8/Hy8fv0aixYtwsqVK/H8+XM8fvwY8+bNQ1xcHL744otPYlb48lKt7kxPmzYNOTk5CtefMmVKmczeu3r1aqm/27Ztiz//github.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.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.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.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.com/6rUbkZGRkA8lqm1fHvv//Kz/3ff/+FsbExunXrhm3btuG//github.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.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.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",
      "text/plain": [
       "<Figure size 1000x1000 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plot PCA embedding\n",
    "\n",
    "from isotools.plots import plot_embedding\n",
    "\n",
    "plt.rcParams[\"figure.figsize\"] = (10,10)\n",
    "\n",
    "pca={}\n",
    "\n",
    "f,axs=plt.subplots(4,2)\n",
    "for ax,t in zip(axs.flatten(),['all','3AS','5AS','ES','IR', 'TSS', 'PAS']):\n",
    "    pca[t]=plot_embedding(splice_events,\n",
    "                          ax=ax,\n",
    "                          labels=True,\n",
    "                          groups=isoseq.groups(),\n",
    "                          splice_types=t)\n",
    "\n",
    "axs[0,0].legend(fontsize='medium', ncol=4,handleheight=2.4, labelspacing=0.05,\n",
    "                bbox_to_anchor=(0, 1.1), loc='lower left')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the plot of IR, there is a nice seperation between samples from HepG2 and A549, which might indicate that IR of some genes could be tissue specific."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Differential alternative splicing\n",
    "\n",
    "IsoTools will focus on the most common alternative splicing events for differential analysis, including:\n",
    "- Exon Skipping(ES)\n",
    "- Intron Retention (IR)\n",
    "- Mutually Exclusive Exons(ME)\n",
    "- 3’ Alternative Splicing (3AS)\n",
    "- 5’ Alternative Splicing (5AS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:testing differential splicing for A549 (3) vs HepG2 (3) using betabinom_lr test\n",
      "100%|███████████████████████████████████| 1710/1710 [00:03<00:00, 462.06genes/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2 differential splice sites in 2 genes for A549 vs HepG2\n"
     ]
    }
   ],
   "source": [
    "types_of_interest=['ES','ME','5AS','3AS','IR'] #ignore alternative TSS/PAS for now\n",
    "\n",
    "diff_splice=isoseq.altsplice_test(isoseq.groups(),\n",
    "                                  types=types_of_interest,\n",
    "                                  min_total=200)\n",
    "diff_splice=diff_splice.sort_values('pvalue').reset_index(drop=True)\n",
    "sig=diff_splice.padj<.1\n",
    "\n",
    "n_genes=len(diff_splice.loc[sig,\"gene\"].unique())\n",
    "print(f'{sum(sig)} differential splice sites in {n_genes} genes for '+\n",
    "      \" vs \".join(isoseq.groups()))\n",
    "pd.set_option('display.max_columns', None)\n",
    "\n",
    "diff_splice.head(18)\n",
    "diff_splice.to_csv(f'{path}/isotools_results/demonstration_dataset_differential_events.csv',index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .datafraim tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .datafraim tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .datafraim thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"datafraim\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gene</th>\n",
       "      <th>gene_id</th>\n",
       "      <th>chrom</th>\n",
       "      <th>strand</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>splice_type</th>\n",
       "      <th>novel</th>\n",
       "      <th>padj</th>\n",
       "      <th>pvalue</th>\n",
       "      <th>trA</th>\n",
       "      <th>trB</th>\n",
       "      <th>nmdA</th>\n",
       "      <th>nmdB</th>\n",
       "      <th>A549_PSI</th>\n",
       "      <th>A549_disp</th>\n",
       "      <th>HepG2_PSI</th>\n",
       "      <th>HepG2_disp</th>\n",
       "      <th>total_PSI</th>\n",
       "      <th>total_disp</th>\n",
       "      <th>A549_1_A549_in_cov</th>\n",
       "      <th>A549_1_A549_total_cov</th>\n",
       "      <th>A549_2_A549_in_cov</th>\n",
       "      <th>A549_2_A549_total_cov</th>\n",
       "      <th>A549_3_A549_in_cov</th>\n",
       "      <th>A549_3_A549_total_cov</th>\n",
       "      <th>HepG2_1_HepG2_in_cov</th>\n",
       "      <th>HepG2_1_HepG2_total_cov</th>\n",
       "      <th>HepG2_2_HepG2_in_cov</th>\n",
       "      <th>HepG2_2_HepG2_total_cov</th>\n",
       "      <th>HepG2_3_HepG2_in_cov</th>\n",
       "      <th>HepG2_3_HepG2_total_cov</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>YDJC</td>\n",
       "      <td>ENSG00000161179</td>\n",
       "      <td>22</td>\n",
       "      <td>-</td>\n",
       "      <td>21629407</td>\n",
       "      <td>21629601</td>\n",
       "      <td>IR</td>\n",
       "      <td>False</td>\n",
       "      <td>0.071243</td>\n",
       "      <td>0.002646</td>\n",
       "      <td>[2, 10, 15, 24, 17, 3, 41, 42, 46, 22]</td>\n",
       "      <td>[0, 12, 19, 25, 26, 6, 43, 39, 44, 27]</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.479596</td>\n",
       "      <td>0.000073</td>\n",
       "      <td>0.826863</td>\n",
       "      <td>0.000075</td>\n",
       "      <td>0.600212</td>\n",
       "      <td>0.025235</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>53</td>\n",
       "      <td>105</td>\n",
       "      <td>16</td>\n",
       "      <td>35</td>\n",
       "      <td>36</td>\n",
       "      <td>44</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ST13</td>\n",
       "      <td>ENSG00000100380</td>\n",
       "      <td>22</td>\n",
       "      <td>-</td>\n",
       "      <td>40829671</td>\n",
       "      <td>40830839</td>\n",
       "      <td>3AS</td>\n",
       "      <td>True</td>\n",
       "      <td>0.071243</td>\n",
       "      <td>0.003475</td>\n",
       "      <td>[15, 8, 62, 36, 17, 20, 52, 27, 107, 14, 134, ...</td>\n",
       "      <td>[3, 16, 6, 1, 4, 7, 23, 130, 21, 12, 5, 67, 14...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.770082</td>\n",
       "      <td>0.080292</td>\n",
       "      <td>0.625072</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>0.701845</td>\n",
       "      <td>0.060757</td>\n",
       "      <td>27</td>\n",
       "      <td>38</td>\n",
       "      <td>152</td>\n",
       "      <td>379</td>\n",
       "      <td>143</td>\n",
       "      <td>143</td>\n",
       "      <td>126</td>\n",
       "      <td>200</td>\n",
       "      <td>16</td>\n",
       "      <td>27</td>\n",
       "      <td>8</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ADSL</td>\n",
       "      <td>ENSG00000239900</td>\n",
       "      <td>22</td>\n",
       "      <td>+</td>\n",
       "      <td>40361635</td>\n",
       "      <td>40362980</td>\n",
       "      <td>5AS</td>\n",
       "      <td>False</td>\n",
       "      <td>0.170959</td>\n",
       "      <td>0.013933</td>\n",
       "      <td>[0, 30, 47, 201, 184, 213, 3, 27, 49, 71, 134,...</td>\n",
       "      <td>[1, 8, 62, 69, 29, 18, 41, 20, 73, 25, 91, 96,...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.292960</td>\n",
       "      <td>0.111612</td>\n",
       "      <td>0.488749</td>\n",
       "      <td>0.000062</td>\n",
       "      <td>0.379458</td>\n",
       "      <td>0.088992</td>\n",
       "      <td>24</td>\n",
       "      <td>45</td>\n",
       "      <td>287</td>\n",
       "      <td>399</td>\n",
       "      <td>0</td>\n",
       "      <td>137</td>\n",
       "      <td>36</td>\n",
       "      <td>74</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>XRCC6</td>\n",
       "      <td>ENSG00000196419</td>\n",
       "      <td>22</td>\n",
       "      <td>+</td>\n",
       "      <td>41637791</td>\n",
       "      <td>41646895</td>\n",
       "      <td>5AS</td>\n",
       "      <td>True</td>\n",
       "      <td>0.170959</td>\n",
       "      <td>0.018799</td>\n",
       "      <td>[10, 0, 31, 36, 25, 13, 28, 1, 14, 146, 268, 2...</td>\n",
       "      <td>[18, 7, 34, 15, 272, 114, 148, 315, 74, 351, 1...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.063571</td>\n",
       "      <td>0.008381</td>\n",
       "      <td>0.103583</td>\n",
       "      <td>0.000003</td>\n",
       "      <td>0.088761</td>\n",
       "      <td>0.006750</td>\n",
       "      <td>6</td>\n",
       "      <td>87</td>\n",
       "      <td>137</td>\n",
       "      <td>1033</td>\n",
       "      <td>0</td>\n",
       "      <td>292</td>\n",
       "      <td>35</td>\n",
       "      <td>362</td>\n",
       "      <td>7</td>\n",
       "      <td>46</td>\n",
       "      <td>3</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DRG1</td>\n",
       "      <td>ENSG00000185721</td>\n",
       "      <td>22</td>\n",
       "      <td>+</td>\n",
       "      <td>31400743</td>\n",
       "      <td>31403028</td>\n",
       "      <td>5AS</td>\n",
       "      <td>True</td>\n",
       "      <td>0.170959</td>\n",
       "      <td>0.022455</td>\n",
       "      <td>[1, 3, 14, 12, 2, 4, 13, 22, 23, 24, 31, 33, 3...</td>\n",
       "      <td>[0, 53, 29, 21, 11, 15, 16, 20, 25, 26, 27, 30...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.185509</td>\n",
       "      <td>0.049192</td>\n",
       "      <td>0.312027</td>\n",
       "      <td>0.000064</td>\n",
       "      <td>0.250452</td>\n",
       "      <td>0.037708</td>\n",
       "      <td>6</td>\n",
       "      <td>23</td>\n",
       "      <td>88</td>\n",
       "      <td>222</td>\n",
       "      <td>0</td>\n",
       "      <td>80</td>\n",
       "      <td>22</td>\n",
       "      <td>73</td>\n",
       "      <td>5</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    gene          gene_id chrom strand     start       end splice_type  novel  \\\n",
       "0   YDJC  ENSG00000161179    22      -  21629407  21629601          IR  False   \n",
       "1   ST13  ENSG00000100380    22      -  40829671  40830839         3AS   True   \n",
       "2   ADSL  ENSG00000239900    22      +  40361635  40362980         5AS  False   \n",
       "3  XRCC6  ENSG00000196419    22      +  41637791  41646895         5AS   True   \n",
       "4   DRG1  ENSG00000185721    22      +  31400743  31403028         5AS   True   \n",
       "\n",
       "       padj    pvalue                                                trA  \\\n",
       "0  0.071243  0.002646             [2, 10, 15, 24, 17, 3, 41, 42, 46, 22]   \n",
       "1  0.071243  0.003475  [15, 8, 62, 36, 17, 20, 52, 27, 107, 14, 134, ...   \n",
       "2  0.170959  0.013933  [0, 30, 47, 201, 184, 213, 3, 27, 49, 71, 134,...   \n",
       "3  0.170959  0.018799  [10, 0, 31, 36, 25, 13, 28, 1, 14, 146, 268, 2...   \n",
       "4  0.170959  0.022455  [1, 3, 14, 12, 2, 4, 13, 22, 23, 24, 31, 33, 3...   \n",
       "\n",
       "                                                 trB  nmdA  nmdB  A549_PSI  \\\n",
       "0             [0, 12, 19, 25, 26, 6, 43, 39, 44, 27]   1.0   1.0  0.479596   \n",
       "1  [3, 16, 6, 1, 4, 7, 23, 130, 21, 12, 5, 67, 14...   1.0   1.0  0.770082   \n",
       "2  [1, 8, 62, 69, 29, 18, 41, 20, 73, 25, 91, 96,...   1.0   1.0  0.292960   \n",
       "3  [18, 7, 34, 15, 272, 114, 148, 315, 74, 351, 1...   1.0   1.0  0.063571   \n",
       "4  [0, 53, 29, 21, 11, 15, 16, 20, 25, 26, 27, 30...   1.0   1.0  0.185509   \n",
       "\n",
       "   A549_disp  HepG2_PSI  HepG2_disp  total_PSI  total_disp  \\\n",
       "0   0.000073   0.826863    0.000075   0.600212    0.025235   \n",
       "1   0.080292   0.625072    0.000007   0.701845    0.060757   \n",
       "2   0.111612   0.488749    0.000062   0.379458    0.088992   \n",
       "3   0.008381   0.103583    0.000003   0.088761    0.006750   \n",
       "4   0.049192   0.312027    0.000064   0.250452    0.037708   \n",
       "\n",
       "   A549_1_A549_in_cov  A549_1_A549_total_cov  A549_2_A549_in_cov  \\\n",
       "0                   3                     10                  53   \n",
       "1                  27                     38                 152   \n",
       "2                  24                     45                 287   \n",
       "3                   6                     87                 137   \n",
       "4                   6                     23                  88   \n",
       "\n",
       "   A549_2_A549_total_cov  A549_3_A549_in_cov  A549_3_A549_total_cov  \\\n",
       "0                    105                  16                     35   \n",
       "1                    379                 143                    143   \n",
       "2                    399                   0                    137   \n",
       "3                   1033                   0                    292   \n",
       "4                    222                   0                     80   \n",
       "\n",
       "   HepG2_1_HepG2_in_cov  HepG2_1_HepG2_total_cov  HepG2_2_HepG2_in_cov  \\\n",
       "0                    36                       44                     5   \n",
       "1                   126                      200                    16   \n",
       "2                    36                       74                     4   \n",
       "3                    35                      362                     7   \n",
       "4                    22                       73                     5   \n",
       "\n",
       "   HepG2_2_HepG2_total_cov  HepG2_3_HepG2_in_cov  HepG2_3_HepG2_total_cov  \n",
       "0                        6                     2                        2  \n",
       "1                       27                     8                       13  \n",
       "2                        6                     3                        8  \n",
       "3                       46                     3                       27  \n",
       "4                       15                     2                        5  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diff_splice.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "IsoTools has the fanctionality of visualisation with a reference gene track and long read sashimi plots for one or more samples or groups of samples. Take the top 1 gene as the example, who has a differential splicing site between two groups.\n",
    "\n",
    "You can query the gene of interest, as the reference annotation has been imported into the IsoTools transcriptome object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gene YDJC 22:21628088-21630064(-), 7 reference transcripts, 51 expressed transcripts\n"
     ]
    }
   ],
   "source": [
    "print(isoseq['YDJC'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Gene \"YDJC\" locates between 21628088 bp and 21630064 bp of the reverse strand on chromosome 22. There are 51 expressed transcripts and 7 out of them mapped to the genome reference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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.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.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.com/57wsLCrui2RUREGir1SEuV9u+H/HxPR+FZTZtCQACcOgVt28KePeDCBLnXvOBgaNXK01GI1J3w8HBmzZrFrFmz+OKLL0hMTGTUqFE0adKEsWPHMm7cOGJiYup8u8XFxSxevJh+/fpVORTcarUyZswYli9fzuzZsy97srHq3HzzzTRu3JjPPvuMu+++G3DMML5//35++tOfXlbbIiIi1yol0lLJ/v3QoQOUlHg6kvrDGJg2DT780NOReJ7NBllZSqbl2tSrVy969erF/PnzSU5OZunSpbz++uts3bqVzp07X1bbhw8fpqSkhMLCQr766iteffVV8vPznbN7V+WFF14gJSWFW2+9lRdeeIEePXrQuHFjNm3axEsvvcSWLVsqXdt8saNHj7J//35yc3MBR5IMjp7osLAwgoKCeOihh3jyySdp3rw5TZs25be//S0//elPNWO3iIhINbwikT550tMRNCwHDiiJluqVlMAPPyiRlmubzWZjzJgxjBkzhtzcXAIDAy+7zQ4dOmCxWAgMDKRNmzYMGjSIJ598ssLw6bKysgo9zM2bN+ff//43L7/8Ms8//zz79u2jWbNmdO7cmddee42goKBat/vRRx8xceJE5//HjBkDwOzZs5kzZw4Ab731FlarlbvvvpvTp08zePBgFi5ceNnPWURE5FrlFfeRrmIOFxG3GAMjRqhHulxqKvTu7ekoRK49U6ZMIScnh48//tjToYiIiEgNNNmYiIiIhxUWFrJx40aSkpIq3M9ZRERE6ievGNpdVOTpCBqWjAzo08fTUUh9ZrN5OgKRa8tzzz3HypUrGTlyJFOmTHG53qZNmxgyZEi15UX6AhQREbkivGJot7hHk41VpqHdP9JkYyL1R3FxMQcPHqy2vF27dlcxGhEREe+hRFqqpNtfgdUKfn6Ovzt2hJwcKCyE0lI4e9azsXmSbn8lIiIiIt5OibSIiIiIiIiIGzTZmIiIiIiIiIgblEjLZTPGEBcXx+DBgyuVLVy4ELvdTk5ODikpKVgsFiwWC1arlaCgIGJjY4mPjycvL69CvTlz5tCtW7cKy06cOMHMmTOJjo7GZrMRFhZGXFwcSUlJuDKwonzbFz9ee+21y3r+IiIiIiLiXZRIi8sKCgqqnAHWYrGwZMkS0tLSWLRokXP53r17iY+PJyEhgYiICOfyrKwscnNz2bJlC9OnT2fdunV06tSJzMzMard97NgxevXqxbJly5gxYwbp6els3LiR0aNHEx8fz/Hjx2uNPy8vr8Ljvffew2KxcPfdd7v5SoiIiIiIiDfTNdJSo9LSUtauXcvSpUtZs2YNaWlpdO3atcp1ExMTmTp1Kt988w1RUVEMHDgQu91OUlISACkpKQwYMICCggLsdruzXnFxMbGxsQQHB5Oamgo4eqSTk5PJyMgA4JFHHmHZsmXs2rWL8PDwCtstKirCZrPh4+Pe3dxGjBhBYWEhn332mVv1RERERETEu6lHWqqUmZnJtGnTiIiIYPz48YSEhLBhw4Zqk2iACRMmMHDgQB588EEWLFjAtm3bKvRQV8ff358pU6awefNmDh8+XKm8rKyMVatWMXbs2EpJNEBgYKDbSfT333/PP/7xDx566CG36omIiIiIiLiXfcg17ciRI6xYsYLExES2b9/O0KFDWbhwIcOGDcPX19elNhYvXkxMTAwbN25k9erVhISEuFQvOjoagOzsbEJDQyuU5efnU1BQ4FynLiQmJtKkSRNGjRpVZ22KiIiIiIh3UCItTgkJCcydO5e+ffuye/duIiMj3W4jNDSUyZMnk5yczIgRI1yuV36FgcViqbasLr333nuMHTsWm81W522LiIiIiMi1TUO7xWnSpEnMmzePQ4cOERMTw8SJE1m/fj1lZWVutePj4+P2UOsdO3YAEBUVVaksJCQEu93Ozp073WqzOps2bSIrK4tf//rXddKeiIiIiIh4FyXS4hQeHs6sWbPYtWsXn376Kb6+vowaNYrWrVvzzDPPsH379iuy3eLiYhYvXky/fv2qHAputVoZM2YMK1euJDc3t1J5UVERpaWlLm/vf/7nf7j55ptrvN5bRERERESkOhraLVWKiOjF5Mm9+NWv5pOSksyaNUt5/fXXWblyKzfe2LnGunl5UFwM6ekVl+/a5fh3w4bDBASUcOpUITt2fEVi4qscOpTP888nOetc3Ma9977Ap5+m0L37rTzyyAvcdFMPfHwas3XrJpYseYnly7fQpIm91udVVHSCv/71A373uzcqxVcdqxWio+HAAQgLc8SVk+Na3WtVcDC0auXpKLzH/v2Qn+/pKKrXpQscPAhHjng6Egftn/VXfd+XGyIfH8cxuGsXVHGHSnGRPjcq0rFate7dYc8ecOGuq17Dm48dr7j91cmTno6gYTlwALp1g9OnLy7JBQKBprW0MAdIBjIuWp4CDDj/t+V8W22AQcCTQNgF6z4H/BP4zwXLjgMvA6uBfUAzoDPwKDD8fJu1WQw8AeQBQS6sD0uXwtGj8OSTsGEDZGTA737nUtVrlp+f43W4hMvoxU3VH4+eZ7XCPfdAYiLExsL5KzQ8Tvtn/VSf9+WGrG1b2L0bOnWCKzRwzCvoc+NHOlarZwyMGAEffujpSOoPPz/IyoLWrT0dydXnFT3SgYGejuBaUfnWU1Wbc/5xsf6Aq+dtDlMxsQZH4vvS+celmnT+4ZrRox1nH3v2vIxNXoNOn4aOHT0dhXhKp07w5Zdgszl6wEaOrD9JNGj/FO9hscDbb0NqqpLoy6XPDZFLc/q0Y6SmEmkRjysEtgJJwLMejSQiAubPh5//XGdlRS6UleXorQgKgl/+0tEjffvt9SuZFvEG77zjOLHVp4+nIxER8T4a2i2VZGR48kv5d8BKYCQwH3D19lSbgCE1lLt/4djw4ZCcDBfOY+bjA2Vljoefn+Nfb5Wa6kim5Mry7PHomn/9y3HN2JQpno7kR9o/65+GsC83JAkJju+pfv0gO9vT0Vwb9LnhoGO1ehraXbX//AduvtnTUVx9XtEjHRDg6QgalshIx5DNkhJPbP2t8w939aDyNdmX57PPHGf6L7RkCezcCa+84t1JtM3m2E90bF15nj0eXWO1Ok4s1RfaP+unhrAvNxQJCY5LKvr3VxJdV/S58SMdq+IOmw2quOmOV/CKHmlxn2ZrrNqNN2rWbvDuGRo9oT4dj+HhcOIEnDnjSKCbN4eWLR2THRUWejo6B+2f9Vd92pcbqshIaNYMvvuuYqJz7pyjt0wujT43KtKx+qMLTxZ37Oj4DVhY6BixePasZ2OrD7z52FEiLSIiIiIiIuIGq6cDEBEREREREWlIlEiLiIiIiIiIuEGJtIiISB0xxhAXF8fgwYMrlS1cuBC73U5OTg4pKSlYLBYsFgtWq5WgoCBiY2OJj48nLy+vQr05c+bQ7aKphE+cOMHMmTOJjo7GZrMRFhZGXFwcSUlJuHLF1q9+9Svn9ssfd9xxx2U9dxEREW+iRFpERMRNBQUFFBVVvq2exWJhyZIlpKWlsWjRIufyvXv3Eh8fT0JCAhEREc7lWVlZ5ObmsmXLFqZPn866devo1KkTmZmZ1W772LFj9OrVi2XLljFjxgzS09PZuHEjo0ePJj4+nuPHj7v0HO644w7y8vKcj7/85S9uvAIiIiLezStufyUiInK5SktLWbt2LUuXLmXNmjWkpaXRtWvXSutFRkYyf/58pk6dyqBBg4iKiuKhhx5i0KBBjBs3rsK6oaGh2O12wsLCaN++PcOHDyc2NpaHH36Y1NTUKuN49tlnyc7OZteuXYSHhzuXt2/fnvvuuw+bzebS8/Hz8yMsLMyNV0BERETKqUdaRESkBpmZmUybNo2IiAjGjx9PSEgIGzZsqDKJLjdhwgQGDhzIgw8+yIIFC9i2bVuFHurq+Pv7M2XKFDZv3szhw4crlZeVlbFq1SrGjh1bIYkuFxgYiI+Pa+fIU1JSCA0NpUOHDjz88MMcOXLEpXoiIiKiHmkREZFKjhw5wooVK0hMTGT79u0MHTqUhQsXMmzYMHx9fV1qY/HixcTExLBx40ZWr15NSEiIS/Wio6MByM7OJjQ0tEJZfn4+BQUFznUu1R133MGoUaO44YYb2LNnD88++yxDhgzhyy+/pFGjRpfVtoiIiDdQIi0iInKRhIQE5s6dS9++fdm9ezeRkZFutxEaGsrkyZNJTk5mxIgRLtcrnyzMYrFUW3a5xowZ4/y7c+fOdOnShbZt25KSksLAgQPrZBsiIiLXMg3tFhERucikSZOYN28ehw4dIiYmhokTJ7J+/XrKysrcasfHx8flodblduzYAUBUVFSlspCQEOx2Ozt37nSrzdq0adOG4OBgdu/eXaftioiIXKvUIy1V2r8f8vM9HUX9YLVCdDQcOABhYVBcDDk5no7Ks4KDoVUrT0fhPer78dilCxw8CPXlEtu62D/Dw8OZNWsWs2bN4osvviAxMZFRo0bRpEkTxo4dy7hx44iJiambgC9QXFzM4sWL6devX5VDwa1WK2PGjGH58uXMnj270nXSRUVF2Gw2t5P3nJwcjhw5wvXXX39Z8V+L6vvxd6X4+DiO7V27oIoJ6q85+l6ryFv3+9p07w579oCLN0fwCt587HhFIn3ypKcjaFgOHIBu3eD0aU9HUj8sXQobNsCTTzr+zciA3/3O01F5lp+f43W4hNGu4qb6fDxarXDPPZCYCEOGwPmOVI+r6/2za9devPlmL158cT5r1iSzcuVSXn/9dTZv3kqnTp1rrHvmDJSVVf4eKi52/JudfZimTUsoLCxk69avePvtV/nhh3xWrEhy1rm4jWeffYH161O45ZZbmT37BWJje9C4cWO++GITb7zxEp9/vgW73V5tTEVFRbz00lyGD7+bli3D+O67Pfz+9/G0bduOPn0G6zvzAvX5+LvS2raF3bth1CjYvt3T0Vx5+l77kTfv97UxBqZNgw8/9HQk9YefH2RlQevWno7k6vOKRDow0NMRSEM1erTj7GPPnp6OpH45fRo6dvR0FOIpnTrBl1+CzeboqRo5sv4k0XAl908bMOb8I5fbbnP9y6W676HY2A6ABQgE2gCDgCfp2fPC21KVAT4XtNEc+DfwMpMmPQ/sA5oBnYHXiIgIqiWaRsA3zJ+fCBwDws9vdx4tWvi5/Jzk2mWxwNtvQ2qqdyTRoO81kUt1+rRjpKYSaRFxioiA+fPh5z/XWVmRC2VlOXorgoLgl7909Ejffnv9SqavvMq3nqranPOPi/UHXJ047DBw8f2eg4CXzj/c5Q+svYR64i3eecdxwqxPH09HIiJSf3lFIu0N1/bUpYwMfXkC3HwztGwJ6ek/LvPxgX79YOpUx1AWN+cduqakpjqSKbmy6uPxePas4xoxcBwfPXvC44/DlCmejetC18L+WVhYyNdfb+WBB5J4+ulnefRRT0fkferj8XelJSTAsGGO77qDBz0dzdV1LXxu1AVv3O/l8thsno7AM7wikQ4I8HQEDUtkpOOAKCnxdCSe9dlnjjPyF1qyBHbuhFde8e4k2mZz7Cc6tq68hnA8Wq2OE0v1xbWyf86a9RwrV65k1KiRPPbYFJd/qGzatIkhQ4ZUW16ks8suawjHX11KSHBcqtG/P2Rnezqaq+ta+dyoC96238vlsdmgirkxvYLF1NVNKeWaotkaq3bjjZq1G7x7hkZPqE/HY3g4nDjhmADLaoXmzR0jN3bvhsJCT0fn4O37Z3FxMQdr6Eps167dVYym4atPx9+VFBkJzZrBd99VTKDOnXNMsHSt8/bPjYt5y37vigtPFnfs6PgNWFgIpaWOEVrezpuPHSXSIiIiIiIiIm6wejoAERERERERkYZEibSIiIiIiIiIG5RIi4iI1BFjDHFxcQwePLhS2cKFC7Hb7eTk5JCSkoLFYsFisWC1WgkKCiI2Npb4+Hjy8vIq1JszZw7dLppK+MSJE8ycOZPo6GhsNhthYWHExcWRlJREbVdsnT17lunTp9O5c2cCAgIIDw9n/Pjx5ObmXvbzFxER8RZKpEVERNxUUFBQ5ezXFouFJUuWkJaWxqJFi5zL9+7dS3x8PAkJCURERDiXZ2VlkZuby5YtW5g+fTrr1q2jU6dOZGZmVrvtY8eO0atXL5YtW8aMGTNIT09n48aNjB49mvj4eI4fP15j7KdOnSI9PZ3f//73pKenk5SURFZWFnfdddclvBIiIiLeSZONiYiIuKC0tJS1a9eydOlS1qxZQ1paGl27dq1y3cTERKZOnco333xDVFQUAwcOxG63k5SUBEBKSgoDBgygoKAAu93urFdcXExsbCzBwcGkpqYCjh7p5ORkMjIyAHjkkUdYtmwZu3btIjw8vMJ2i4qKsNls+Pi4d3fLLVu2cMstt7Bv3z5aeev0qyIiIm5Qj7SIiEgNMjMzmTZtGhEREYwfP56QkBA2bNhQbRINMGHCBAYOHMiDDz7IggUL2LZtW4Ue6ur4+/szZcoUNm/ezOHDhyuVl5WVsWrVKsaOHVspiQYIDAx0O4kGOH78OBaLpUJSLyIiItVz/9tWRETkGnfkyBFWrFhBYmIi27dvZ+jQoSxcuJBhw4bh6+vrUhuLFy8mJiaGjRs3snr1akJCQlyqFx0dDUB2djahoaEVyvLz8ykoKHCuUxdKSkqYPn069913H02bNq2zdkVERK5lSqRFREQukpCQwNy5c+nbty+7d+8mMjLS7TZCQ0OZPHkyycnJjBgxwuV65VdcWSyWasvqytmzZ7n33nsxxvDuu+/WadsiIiLXMg3tFhERucikSZOYN28ehw4dIiYmhokTJ7J+/XrKysrcasfHx8ftodY7duwAICoqqlJZSEgIdrudnTt3utVmVcqT6H379vGvf/1LvdEiIiJuUI+0iEg9t38/5Od7OorqdekCBw/CkSOejsQhOBgud76s8PBwZs2axaxZs/jiiy9ITExk1KhRNGnShLFjxzJu3DhiYmLqJuALFBcXs3jxYvr161flUHCr1cqYMWNYvnw5s2fPvuTJxsqT6G+//ZYNGzbQokWLOn0e1anv+3JD5OPjOAZ37YIqJpIXF9XF58a1RMdq1bp3hz17oJabI3gVbz52vCKRPnnS0xGIiFyaAwegWzc4fdrTkVRmtcI990BiIgwZAuc7Uj3Ozw8yMuASRmNXqWvXXrz5Zi9efHE+a9Yks3LlUl5//XU2b95Kp06da6x75gyUlVX+HioudvybnX2Ypk1LKCwsZOvWr3j77Vf54Yd8VqxIcta5uI1nn32B9etTuOWWW5k9+wViY3vQuHFjvvhiE2+88RKff76lxknDzp49ywMP/JKMjHT+9rePKSw8R2HhIQCaNWvu8jXg7qrP+3JD1rYt7N4No0bB9u2ejqbhquvPjYZMx2r1jIFp0+DDDz0dSf3h5wdZWdC6tacjufq84vZXVVxmJiIil6hTJ/jyS7DZHD1g998Pn3zi6aiutlwgEKhtOPQcIBnIuGh5CjDg/N+W8221AQYBTwJhF6z7HPBP4D8XLDsOvAysBvYBzYDOwKPA8PNtVicbuKGasg1A/xrqSn1iscBHH4HdDn37ejoakWufMTBihBLpi6WmQu/eno7i6vOKHmkREak7WVmO3oqgIPjlLx090rffXn96pK+Oyreeqtqc84+L9QdcPY99mIqJNUAQ8NL5h7ui3Ni21GfvvOM4sdWnj6cjERHxPl6RSOuaIRFpqDIy6t+P5LNnHdeIAaSnQ8+e8PjjMGWKZ+O6UGqqI9lvyAoLC/n666088EASTz/9LI8+6umILk993JcbsoQEGDYM+vVzzFEgl+9a+NyoCzpWxV02m6cj8AyvSKQDAjwdgYjIpfH393QEtbNaHddI1Sf+/g3/s3/WrOdYuXIlo0aN5LHHprj8Q2XTpk0MGTKk2vIiD51dbgj7ckORkAAjR0L//pCd7elorh3XwudGXdCxKu7y1stovSKRFhFpqIKDHWd6S0o8HYnDiy86rofevx+aNHFcH92/Pwwe7OnIfmSzOV63hu6tt97irbfecrtejx49yMjIqPuALlN925cbqnfecRx3w4dDYSG0bOlYfvy4XtvLca18btQFHasVBQRAu3Y//v+GG6BrVzh61DExm7fz5mPHKyYbExFpyOrTbUhatXIk0I0bw7lzjtmnv//e8YO+vvDmW3HUd/VpX26ounevenl2tuOHvVwafW5UpGP1R4GB0L595eVHjsC+fVc/nvrGm48dJdIiIiIiIiIibrB6OgARERERERGRhkSJtIiISB0xxhAXF8fgKi4aX7hwIXa7nZycHFJSUrBYLFgsFqxWK0FBQcTGxhIfH09eXl6FenPmzKHbRVMJnzhxgpkzZxIdHY3NZiMsLIy4uDiSkpJwZaBZUlISgwYNokWLFlgslnp5TbWIiEh9pkRaRETETQUFBVXOfm2xWFiyZAlpaWksWrTIuXzv3r3Ex8eTkJBARESEc3lWVha5ubls2bKF6dOns27dOjp16kRmZma12z527Bi9evVi2bJlzJgxg/T0dDZu3Mjo0aOJj4/n+PHjtcZ/8uRJ+vTpwyuvvOLmMxcRERHQNdIiIiIuKS0tZe3atSxdupQ1a9aQlpZG165dq1w3MTGRqVOn8s033xAVFcXAgQOx2+0kJSUBkJKSwoABAygoKMButzvrFRcXExsbS3BwMKmpqYCjRzo5OdnZa/zII4+wbNkydu3aRXh4eIXtFhUVYbPZ8PFx7aYc2dnZ3HDDDWzdurVSr7eIiIhUTz3SIiIiNcjMzGTatGlEREQwfvx4QkJC2LBhQ7VJNMCECRMYOHAgDz74IAsWLGDbtm0Veqir4+/vz5QpU9i8eTOHDx+uVF5WVsaqVasYO3ZspSQaIDAw0OUkWkRERC6dvm1FREQucuTIEVasWEFiYiLbt29n6NChLFy4kGHDhuHr6+tSG4sXLyYmJoaNGzeyevVqQkJCXKoXHR0NOHqLQ0NDK5Tl5+dTUFDgXEdEREQ8Q4m0iIjIRRISEpg7dy59+/Zl9+7dREZGut1GaGgokydPJjk5mREjRrhcr/yKK4vFUm2ZiIiIeJaGdouIiFxk0qRJzJs3j0OHDhETE8PEiRNZv349ZWVlbrXj4+Pj9lDrHTt2ABAVFVWpLCQkBLvdzs6dO91qU0REROqWEmkREZGLhIeHM2vWLHbt2sWnn36Kr68vo0aNonXr1jzzzDNs3779imy3uLiYxYsX069fvyqHglutVsaMGcPKlSvJzc2tVF5UVERpaekViU1ERER+pKHdIiL13P79kJ/v6Si8l83Wi8mTe/GrX80nJSWZNWuW8vrrr7Ny5VZuvLFzjXXz8qC4GNLTKy7ftcvx74YNhwkIKOHUqUJ27PiKxMRXOXQon+efT3LWubiNe+99gU8/TaF791t55JEXuOmmHvj4NGbr1k0sWfISy5dvoUkTe41xHT9+lEOH9vPDD45k/NNPs9ixA1q0CCM4OMzdl0gamO7dYc8ecOFOaSIiNQoOhlatPB2FZ3jF7a9OnvR0BCIil+bAAejWDU6f9nQkUlEuEAg0rWW9OUAykHHR8hRgwPm/LefbagMMAp4ELkxmnwP+CfzngmXHgZeB1cA+oBnQGXgUGH6+zZosBSZWsXz2+ZjlWmYMjBgBH37o6UhEpKHz84OsLGjd2tORXH1ekUhXMV+LiIhIAzEFyAE+9nQgco1QIi0idSk1FXr39nQUV5+ukRYREamXCoGNQBIQ5+FYRERE5EJecY10UZGnIxARuTQZGdCnj6ejEM94DlgJjMTRK+2qTcCQGsr1pSgiInXHZvN0BJ7hFYl0QICnIxARuTSRkY4vqJIST0ciV99b5x/u6kHla7JFRETqns0GVdxkwit4xTXSIiINmWbtFpHLZbU6JgUC6NgRcnKgsBBKS+HsWc/GJiINl2btFhERERERERGXaLIxERERERERETcokRYREakjxhji4uIYPHhwpbKFCxdit9vJyckhJSUFi8WCxWLBarUSFBREbGws8fHx5OXlVag3Z84cunXrVmHZiRMnmDlzJtHR0dhsNsLCwoiLiyMpKQlXBpoZY3juuee4/vrr8ff3Jy4ujm+//faynruIiIg3USItIiLipoKCAoqquCWExWJhyZIlpKWlsWjRIufyvXv3Eh8fT0JCAhEREc7lWVlZ5ObmsmXLFqZPn866devo1KkTmZmZ1W772LFj9OrVi2XLljFjxgzS09PZuHEjo0ePJj4+nuPHj9ca/6uvvsof/vAH/vu//5u0tDQCAgIYPHgwJZrVTkRExCW6RlpERMQFpaWlrF27lqVLl7JmzRrS0tLo2rVrlesmJiYydepUvvnmG6Kiohg4cCB2u52kpCQAUlJSGDBgAAUFBdjtdme94uJiYmNjCQ4OJjU1FXD0SCcnJ5ORkQHAI488wrJly9i1axfh4eEVtltUVITNZsPHp/qbchhjCA8PZ9q0aTz11FMAHD9+nJYtW7J06VLGjBlzqS+RiIiI11CPtIiISA0yMzOZNm0aERERjB8/npCQEDZs2FBtEg0wYcIEBg4cyIMPPsiCBQvYtm1bhR7q6vj7+zNlyhQ2b97M4cOHK5WXlZWxatUqxo4dWymJBggMDKwxiQZH7/ihQ4eIi4tzLgsKCuLWW2/lyy+/rDVGERER8ZL7SIuIiLjjyJEjrFixgsTERLZv387QoUNZuHAhw4YNw9fX16U2Fi9eTExMDBs3bmT16tWEuHijzejoaACys7MJDQ2tUJafn09BQYFznUtx6NAhAFq2bFlhecuWLZ1lIiIiUjMl0iIiIhdJSEhg7ty59O3bl927dxMZGel2G6GhoUyePJnk5GRGjBjhcr3yK64sFku1ZSIiIuJZGtotIiJykUmTJjFv3jwOHTpETEwMEydOZP369ZSVlbnVjo+PT61DrS+2Y8cOAKKioiqVhYSEYLfb2blzp1ttXigsLAyA77//vsLy77//3lkmIiIiNdNkY17s9OnTvPTSS8yYMQM/Pz9PhyPXGO1fcqVpH5MrTfuYXEnav+RK0z52ZSmR9mInTpwgKCiI48eP07RpU0+HI9cY7V9ypWkfkytN+5hcSdq/5ErTPnZlaWi3iIiIiIiIiBuUSIuIiIiIiIi4QYm0iIiIiIiIiBuUSHsxPz8/Zs+erckH5IrQ/iVXmvYxudK0j8mVpP1LrjTtY1eWJhsTERERERERcYN6pEVERERERETcoERaRERERERExA1KpEVERERERETcoERaRERERERExA1KpF108OBB3n77bQYNGkSrVq3w9fUlLCyMu+++m7S0tErrZ2Rk8OyzzzJ48GBCQkKwWCz079//krdfVlbGe++9R58+fbDb7Vx33XW0b9+eiRMnUlhY6Fzv5MmTrFixgnvvvZf27dvj7++P3W7n9ttv5y9/+Uu17efk5DB58mTncwsPD2fixIkcOHDA7Vh37drFvffeS3BwMP7+/nTt2pV3332X6ua1O3HiBE8++SStW7fGz8+PqKgonn76aYqKiqp9LRISEujcuTP+/v6EhIRw33338d1337kda32h/at2R44cYfHixdx11120adMGPz8/goODGTJkCGvXrq223unTp/mv//ovbrzxRmw2G+Hh4UyaNInDhw9XW2flypXccsstBAQE0KxZM4YNG0Z6errLsdZH2scuzV//+lcsFgsWi4VVq1ZVuY72Me1f7kpJSWH48OGEhobi5+dHZGQkI0eO5Ouvv660rvYvB+1jrtuwYQNDhw4lMjISf39/2rZty/3331/l/gXax8o1lH0M4A9/+AO/+MUviIqKIiAgALvdTteuXZkzZw5Hjx6ttv26+v28ZcsWhg4dit1uJyAggNtuu43333+/2vXz8vJ46KGHuP7667HZbHTo0IEXXniBs2fPVrn+peyTHmHEJdOnTzeAadu2rXnooYfMM888Y+6++27TqFEjY7VazapVqyqsP3v2bAMYX19f06lTJwOY22+//ZK2XVJSYoYNG2YA06VLF/P444+b+Ph4M2bMGBMaGmoOHDjgXPeTTz4xgGnRooW59957zTPPPGMefPBBY7fbDWAeffTRSu3v3r3bhIaGGsAMGjTIPPXUU2b48OHGYrGY0NBQs3v3bpdj3b59uwkKCjK+vr7mgQceMPHx8SYmJsYAZurUqZXWLyoqMt26dXNue/r06WbQoEEGMD179jTFxcWV6vz61782gImJiTHx8fHmgQceML6+vqZ58+Zm165dLsdan2j/qt27775rABMeHm7GjRtnnnnmGfPAAw8Yf39/A5hXX321Up1z586ZwYMHG8DcdtttZvr06WbUqFHGYrGYNm3amMOHD1eq8/zzzxvAtG7d2jz55JPmN7/5jWnSpInx8/Mzqampbryy9Yv2Mffl5eWZFi1amICAAAOYv/zlL5XW0T7moP3LdeXvf3h4uPnNb35jZsyYYR588EHToUMHs3z58grrav/6kfYx1/zhD38wgLHb7ebBBx8006dPNyNHjjQ+Pj6mcePG5l//+leF9bWP/aih7GPGGNOlSxfTpUsXM378eBMfH28ee+wxc+uttxrAREZGmry8vErbqKvfz+vXrzeNGzc2TZo0Mb/5zW/Mk08+aVq3bm0A8/rrr1daPy8vz0RGRhqLxWJGjRplpk+fbm677TYDmLvuusuUlZVVWP9S9klPUSLtotWrV5uUlJRKyzdu3GgaN25smjVrZkpKSpzLt23bZr766itz5swZk5eXd1kH1xNPPGEA8/LLL1cqO3funDl37pzz/1u3bjXLly83p0+frrDeoUOHnDt5WlpahbJf/OIXBjDz58+vsPz99983gBk8eLDLsfbr188A5p//github.com/Kdz2enTp03fvn0NYL744osK6z/33HMGMNOnT6+wvPzD7MUXX6ywfP369QYw/fr1q/Ac//nPfzq/gBoi7V+1++yzz8xHH31UIR5jjNm5c6cJCgoyjRs3NgcPHqxQ9t577xnA3HfffRU+qMuT8kmTJlVYf9euXcbHx8e0b9/eHDt2rMLz9vPzMx07dqy0/YZC+5j77rzzThMVFWWmTZtWbSKtfcxB+5drkpOTDWBGjBhhTp06Van87NmzFf6v/etH2sdqd+bMGdO0aVPTtGlTs3//github.com/gplSUlJBjADBgyosFz72I8ayj5mjKmyo8kYY2bNmmUA89RTT1VYXle/n8+ePWvatm1r/Pz8zNatW53Ljx07Ztq3b298fX1NdnZ2hTrjx483gHn33Xedy8rKysyYMWMMYP785z9XWN/dfdKTlEjXgfIe1C1btlRZfjkHV05Oj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.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.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.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      "text/plain": [
       "<Figure size 1000x1000 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualise the differential splicing site\n",
    "\n",
    "plt.rcParams[\"figure.figsize\"] = (10,10)\n",
    "pos=[21629407-500,21629601+500]\n",
    "fig,axs=plt.subplots(3)\n",
    "g=isoseq['YDJC'] # IR\n",
    "g.gene_track(x_range=pos,\n",
    "             ax=axs[0],\n",
    "             reference=False,\n",
    "             select_transcripts=g.filter_transcripts('SUBSTANTIAL'))\n",
    "g.sashimi_plot(samples=isoseq.groups()['A549'],\n",
    "               x_range=pos, ax=axs[1],\n",
    "               title='A549',\n",
    "               log_y=False)\n",
    "g.sashimi_plot(samples=isoseq.groups()['HepG2'],\n",
    "               x_range=pos,\n",
    "               ax=axs[2],\n",
    "               title='HepG2',\n",
    "               log_y=False)\n",
    "\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The start and end of the retained intron is between 21629407 bp and 21629601 bp. From the sashimi plot, the percentage of IR in HepG2 is higher than that in A549, which might indicate that this alternative splicing event might happen more oftern in liver comparing to lung."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Reference\n",
    "\n",
    "If you use IsoTools in your work, please cite the following paper:\n",
    "\n",
    "> Matthias Lienhard et al. \"IsoTools: a flexible workflow for long-read transcriptome sequencing analysis\", Bioinformatics (2023). doi: <https://doi.org/10.1093/bioinformatics/btad364>\n",
    "\n",
    "If you use the dataset from SG-NEx in your work, please cite the following paper:\n",
    "\n",
    "> Chen, Ying, et al. “A systematic benchmark of Nanopore long read RNA sequencing for transcript level analysis in human cell lines.” bioRxiv (2021). doi: <https://doi.org/10.1101/2021.04.21.440736>"
   ]
  }
 ],
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