{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Sample Queries from Amazon Omics Analytics\n",
    "\n",
    "In this notebook, we will demonstrate some sample genomics queries using the Ovation Dx non-alcoholic fatty liver disease (NAFLD) example dataset (10 samples) that is available on the AWS Data Exchange. We also use variant annotations from ClinVar. \n",
    "\n",
    "### Pre-requisites\n",
    "1. The variants and annotations have already been imported into the Omics Variant store and Annotation store\n",
    "2. Appropriate resource links have been created in AWS Lake Formation.\n",
    "3. The SageMaker instance role for this notebook has the necessary permissions in AWS Lake Formation.\n",
    "4. We are using an Athena query engine Version 3 workgroup.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import Dependencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Looking in indexes: https://pypi.org/simple, https://pip.repos.neuron.amazonaws.com\n",
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      "Requirement already satisfied: six>=1.5 in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (from python-dateutil<3.0.0,>=2.1->botocore>=1.24.7->PyAthena) (1.16.0)\n",
      "Installing collected packages: botocore, PyAthena\n",
      "  Attempting uninstall: botocore\n",
      "    Found existing installation: botocore 1.24.19\n",
      "    Uninstalling botocore-1.24.19:\n",
      "      Successfully uninstalled botocore-1.24.19\n",
      "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
      "awscli 1.25.83 requires botocore==1.27.82, but you have botocore 1.27.96 which is incompatible.\n",
      "aiobotocore 2.0.1 requires botocore<1.22.9,>=1.22.8, but you have botocore 1.27.96 which is incompatible.\u001b[0m\u001b[31m\n",
      "\u001b[0mSuccessfully installed PyAthena-2.14.0 botocore-1.27.96\n",
      "\u001b[33mWARNING: You are using pip version 22.0.4; however, version 22.3.1 is available.\n",
      "You should consider upgrading via the '/home/ec2-user/anaconda3/envs/python3/bin/python -m pip install --upgrade pip' command.\u001b[0m\u001b[33m\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "import boto3, os\n",
    "import pandas as pd\n",
    "\n",
    "s3 = boto3.resource('s3')\n",
    "import sys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "Installing collected packages: asn1crypto, aenum, scramp, python-utils, pymysql, numpy, jsonpath-ng, isodate, backoff, requests-aws4auth, progressbar2, pg8000, opensearch-py, gremlinpython, redshift-connector, awswrangler\n",
      "  Attempting uninstall: asn1crypto\n",
      "    Found existing installation: asn1crypto 1.4.0\n",
      "    Uninstalling asn1crypto-1.4.0:\n",
      "      Successfully uninstalled asn1crypto-1.4.0\n",
      "  Attempting uninstall: numpy\n",
      "    Found existing installation: numpy 1.20.3\n",
      "    Uninstalling numpy-1.20.3:\n",
      "      Successfully uninstalled numpy-1.20.3\n",
      "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
      "daal4py 2021.3.0 requires daal==2021.2.3, which is not installed.\n",
      "numba 0.54.1 requires numpy<1.21,>=1.17, but you have numpy 1.23.4 which is incompatible.\u001b[0m\u001b[31m\n",
      "\u001b[0mSuccessfully installed aenum-3.1.11 asn1crypto-1.5.1 awswrangler-2.17.0 backoff-2.2.1 gremlinpython-3.6.1 isodate-0.6.1 jsonpath-ng-1.5.3 numpy-1.23.4 opensearch-py-2.0.0 pg8000-1.29.3 progressbar2-4.2.0 pymysql-1.0.2 python-utils-3.4.5 redshift-connector-2.0.909 requests-aws4auth-1.1.2 scramp-1.4.4\n",
      "\u001b[33mWARNING: You are using pip version 22.0.4; however, version 22.3.1 is available.\n",
      "You should consider upgrading via the '/home/ec2-user/anaconda3/envs/python3/bin/python -m pip install --upgrade pip' command.\u001b[0m\u001b[33m\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "!{sys.executable} -m pip install awswrangler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Looking in indexes: https://pypi.org/simple, https://pip.repos.neuron.amazonaws.com\n",
      "Collecting plotnine\n",
      "  Downloading plotnine-0.10.1-py3-none-any.whl (1.2 MB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.2/1.2 MB\u001b[0m \u001b[31m56.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hCollecting mizani>=0.8.1\n",
      "  Downloading mizani-0.8.1-py3-none-any.whl (64 kB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m64.7/64.7 KB\u001b[0m \u001b[31m5.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hRequirement already satisfied: scipy>=1.5.0 in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (from plotnine) (1.5.3)\n",
      "Requirement already satisfied: matplotlib>=3.5.0 in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (from plotnine) (3.5.0)\n",
      "Collecting statsmodels>=0.13.2\n",
      "  Downloading statsmodels-0.13.5-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (9.9 MB)\n",
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      "\u001b[?25hRequirement already satisfied: patsy>=0.5.1 in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (from plotnine) (0.5.2)\n",
      "Requirement already satisfied: numpy>=1.19.0 in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (from plotnine) (1.23.4)\n",
      "Collecting pandas>=1.3.5\n",
      "  Downloading pandas-1.5.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.2 MB)\n",
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      "\u001b[?25hRequirement already satisfied: cycler>=0.10 in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (from matplotlib>=3.5.0->plotnine) (0.11.0)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (from matplotlib>=3.5.0->plotnine) (2.8.2)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (from matplotlib>=3.5.0->plotnine) (4.28.2)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (from matplotlib>=3.5.0->plotnine) (1.3.2)\n",
      "Requirement already satisfied: pyparsing>=2.2.1 in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (from matplotlib>=3.5.0->plotnine) (3.0.6)\n",
      "Requirement already satisfied: pillow>=6.2.0 in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (from matplotlib>=3.5.0->plotnine) (9.0.1)\n",
      "Requirement already satisfied: packaging>=20.0 in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (from matplotlib>=3.5.0->plotnine) (21.3)\n",
      "Collecting palettable\n",
      "  Downloading palettable-3.3.0-py2.py3-none-any.whl (111 kB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m111.8/111.8 KB\u001b[0m \u001b[31m21.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hCollecting backports.zoneinfo\n",
      "  Downloading backports.zoneinfo-0.2.1-cp38-cp38-manylinux1_x86_64.whl (74 kB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m74.0/74.0 KB\u001b[0m \u001b[31m15.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hRequirement already satisfied: pytz>=2020.1 in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (from pandas>=1.3.5->plotnine) (2021.3)\n",
      "Requirement already satisfied: six in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (from patsy>=0.5.1->plotnine) (1.16.0)\n",
      "Installing collected packages: palettable, backports.zoneinfo, pandas, statsmodels, mizani, plotnine\n",
      "  Attempting uninstall: pandas\n",
      "    Found existing installation: pandas 1.3.4\n",
      "    Uninstalling pandas-1.3.4:\n",
      "      Successfully uninstalled pandas-1.3.4\n",
      "  Attempting uninstall: statsmodels\n",
      "    Found existing installation: statsmodels 0.13.1\n",
      "    Uninstalling statsmodels-0.13.1:\n",
      "      Successfully uninstalled statsmodels-0.13.1\n",
      "Successfully installed backports.zoneinfo-0.2.1 mizani-0.8.1 palettable-3.3.0 pandas-1.5.1 plotnine-0.10.1 statsmodels-0.13.5\n",
      "\u001b[33mWARNING: You are using pip version 22.0.4; however, version 22.3.1 is available.\n",
      "You should consider upgrading via the '/home/ec2-user/anaconda3/envs/python3/bin/python -m pip install --upgrade pip' command.\u001b[0m\u001b[33m\n",
      "\u001b[0mNote: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install plotnine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "import awswrangler as wr\n",
    "import pandas as pd\n",
    "from datetime import datetime\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will use plotnine for visualizations using ggplot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "from plotnine import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>contigname</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>names</th>\n",
       "      <th>referenceallele</th>\n",
       "      <th>alternatealleles</th>\n",
       "      <th>qual</th>\n",
       "      <th>filters</th>\n",
       "      <th>splitfrommultiallelic</th>\n",
       "      <th>attributes</th>\n",
       "      <th>sampleid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10</td>\n",
       "      <td>68443355</td>\n",
       "      <td>68443356</td>\n",
       "      <td>[1205277]</td>\n",
       "      <td>G</td>\n",
       "      <td>[A]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>[(CLNSIG, Likely_benign), (GENEINFO, DNA2:1763...</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10</td>\n",
       "      <td>68444615</td>\n",
       "      <td>68444616</td>\n",
       "      <td>[669719]</td>\n",
       "      <td>T</td>\n",
       "      <td>[C]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>[(RS, 4237317), (CLNSIG, Benign), (GENEINFO, D...</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10</td>\n",
       "      <td>68444724</td>\n",
       "      <td>68444725</td>\n",
       "      <td>[1282137]</td>\n",
       "      <td>C</td>\n",
       "      <td>[CA]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>[(CLNSIG, Benign), (GENEINFO, DNA2:1763), (CLN...</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10</td>\n",
       "      <td>68444724</td>\n",
       "      <td>68444726</td>\n",
       "      <td>[1182344]</td>\n",
       "      <td>CA</td>\n",
       "      <td>[C]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>[(CLNSIG, Benign), (GENEINFO, DNA2:1763), (CLN...</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10</td>\n",
       "      <td>68444738</td>\n",
       "      <td>68444739</td>\n",
       "      <td>[1225885]</td>\n",
       "      <td>A</td>\n",
       "      <td>[G]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>[(CLNSIG, Benign), (GENEINFO, DNA2:1763), (CLN...</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10</td>\n",
       "      <td>68444758</td>\n",
       "      <td>68444759</td>\n",
       "      <td>[669718]</td>\n",
       "      <td>G</td>\n",
       "      <td>[T]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>[(RS, 4237318), (CLNSIG, Benign), (GENEINFO, D...</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>10</td>\n",
       "      <td>68444902</td>\n",
       "      <td>68444903</td>\n",
       "      <td>[1397917]</td>\n",
       "      <td>T</td>\n",
       "      <td>[C]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>[(CLNSIG, Uncertain_significance), (GENEINFO, ...</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10</td>\n",
       "      <td>68444918</td>\n",
       "      <td>68444919</td>\n",
       "      <td>[1324261]</td>\n",
       "      <td>A</td>\n",
       "      <td>[G]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>[(CLNSIG, Likely_pathogenic), (GENEINFO, DNA2:...</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>10</td>\n",
       "      <td>68444927</td>\n",
       "      <td>68444928</td>\n",
       "      <td>[1698835]</td>\n",
       "      <td>A</td>\n",
       "      <td>[G]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>[(CLNSIG, Uncertain_significance), (GENEINFO, ...</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>68444985</td>\n",
       "      <td>68444986</td>\n",
       "      <td>[444217]</td>\n",
       "      <td>T</td>\n",
       "      <td>[C]</td>\n",
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       "      <td>False</td>\n",
       "      <td>[(RS, 530452383), (CLNSIG, Uncertain_significa...</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  contigname     start       end      names referenceallele alternatealleles  \\\n",
       "0         10  68443355  68443356  [1205277]               G              [A]   \n",
       "1         10  68444615  68444616   [669719]               T              [C]   \n",
       "2         10  68444724  68444725  [1282137]               C             [CA]   \n",
       "3         10  68444724  68444726  [1182344]              CA              [C]   \n",
       "4         10  68444738  68444739  [1225885]               A              [G]   \n",
       "5         10  68444758  68444759   [669718]               G              [T]   \n",
       "6         10  68444902  68444903  [1397917]               T              [C]   \n",
       "7         10  68444918  68444919  [1324261]               A              [G]   \n",
       "8         10  68444927  68444928  [1698835]               A              [G]   \n",
       "9         10  68444985  68444986   [444217]               T              [C]   \n",
       "\n",
       "   qual filters  splitfrommultiallelic  \\\n",
       "0   NaN    None                  False   \n",
       "1   NaN    None                  False   \n",
       "2   NaN    None                  False   \n",
       "3   NaN    None                  False   \n",
       "4   NaN    None                  False   \n",
       "5   NaN    None                  False   \n",
       "6   NaN    None                  False   \n",
       "7   NaN    None                  False   \n",
       "8   NaN    None                  False   \n",
       "9   NaN    None                  False   \n",
       "\n",
       "                                          attributes sampleid  \n",
       "0  [(CLNSIG, Likely_benign), (GENEINFO, DNA2:1763...     <NA>  \n",
       "1  [(RS, 4237317), (CLNSIG, Benign), (GENEINFO, D...     <NA>  \n",
       "2  [(CLNSIG, Benign), (GENEINFO, DNA2:1763), (CLN...     <NA>  \n",
       "3  [(CLNSIG, Benign), (GENEINFO, DNA2:1763), (CLN...     <NA>  \n",
       "4  [(CLNSIG, Benign), (GENEINFO, DNA2:1763), (CLN...     <NA>  \n",
       "5  [(RS, 4237318), (CLNSIG, Benign), (GENEINFO, D...     <NA>  \n",
       "6  [(CLNSIG, Uncertain_significance), (GENEINFO, ...     <NA>  \n",
       "7  [(CLNSIG, Likely_pathogenic), (GENEINFO, DNA2:...     <NA>  \n",
       "8  [(CLNSIG, Uncertain_significance), (GENEINFO, ...     <NA>  \n",
       "9  [(RS, 530452383), (CLNSIG, Uncertain_significa...     <NA>  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = wr.athena.read_sql_query(\"SELECT * FROM clinvar limit 10\", database=\"ovation_claims\", workgroup = \"athena3\")\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us join the variants to clinical annotations from ClinVar, and filter only for those that have a \"Pathogenic\", \"Likely_pathogenic\" or \"Uncertain_significance\" ACMG variant classifications from ClinVar. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = wr.athena.read_sql_query(\"SELECT variants.sampleid,variants.contigname,variants.start,\\\n",
    "variants.\\\"end\\\",variants.referenceallele,variants.alternatealleles,variants.attributes as variant_attributes,\\\n",
    "clinvar.attributes['CLNSIG'] as clinical_significance, \\\n",
    "SPLIT(clinvar.attributes['GENEINFO'],':')[1] as gene, \\\n",
    "SPLIT(clinvar.attributes['CLNDN'],'|')[1] as disorder \\\n",
    "FROM ovation_variants as variants \\\n",
    "INNER JOIN clinvar as clinvar ON \\\n",
    "variants.contigname=CONCAT('chr',clinvar.contigname) AND variants.start=clinvar.start AND variants.\\\"end\\\"=clinvar.\\\"end\\\" AND variants.referenceallele=clinvar.referenceallele AND variants.alternatealleles=clinvar.alternatealleles \\\n",
    "WHERE (clinvar.attributes['CLNSIG']='Pathogenic' OR clinvar.attributes['CLNSIG'] ='Likely_pathogenic' OR clinvar.attributes['CLNSIG']='Uncertain_significance')\",\\\n",
    "                              database=\"ovation_claims\", workgroup = \"athena3\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sampleid</th>\n",
       "      <th>contigname</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>referenceallele</th>\n",
       "      <th>alternatealleles</th>\n",
       "      <th>variant_attributes</th>\n",
       "      <th>clinical_significance</th>\n",
       "      <th>gene</th>\n",
       "      <th>disorder</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>zr5654_4_S1</td>\n",
       "      <td>chr16</td>\n",
       "      <td>66508712</td>\n",
       "      <td>66508713</td>\n",
       "      <td>T</td>\n",
       "      <td>[C]</td>\n",
       "      <td>[(CSQ, C|downstream_gene_variant|MODIFIER|TK2|...</td>\n",
       "      <td>Uncertain_significance</td>\n",
       "      <td>TK2</td>\n",
       "      <td>Mitochondrial_DNA_depletion_syndrome,_myopathi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>zr5654_22_S13</td>\n",
       "      <td>chr17</td>\n",
       "      <td>5028784</td>\n",
       "      <td>5028785</td>\n",
       "      <td>C</td>\n",
       "      <td>[CT]</td>\n",
       "      <td>[(CSQ, T|downstream_gene_variant|MODIFIER|SLC5...</td>\n",
       "      <td>Uncertain_significance</td>\n",
       "      <td>KIF1C</td>\n",
       "      <td>not_provided</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>zr5654_9_S5</td>\n",
       "      <td>chr16</td>\n",
       "      <td>47700347</td>\n",
       "      <td>47700349</td>\n",
       "      <td>CA</td>\n",
       "      <td>[C]</td>\n",
       "      <td>[(CSQ, -|3_prime_UTR_variant|MODIFIER|PHKB|ENS...</td>\n",
       "      <td>Uncertain_significance</td>\n",
       "      <td>PHKB</td>\n",
       "      <td>Glycogen_phosphorylase_kinase_deficiency</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>zr5654_10_S6</td>\n",
       "      <td>chr3</td>\n",
       "      <td>49416994</td>\n",
       "      <td>49416995</td>\n",
       "      <td>G</td>\n",
       "      <td>[A]</td>\n",
       "      <td>[(CSQ, A|upstream_gene_variant|MODIFIER|RHOA|E...</td>\n",
       "      <td>Uncertain_significance</td>\n",
       "      <td>AMT</td>\n",
       "      <td>Non-ketotic_hyperglycinemia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>zr5654_7_S3</td>\n",
       "      <td>chr5</td>\n",
       "      <td>137618888</td>\n",
       "      <td>137618891</td>\n",
       "      <td>ATT</td>\n",
       "      <td>[A]</td>\n",
       "      <td>[(CSQ, -|3_prime_UTR_variant|MODIFIER|KLHL3|EN...</td>\n",
       "      <td>Uncertain_significance</td>\n",
       "      <td>KLHL3</td>\n",
       "      <td>Autosomal_dominant_pseudohypoaldosteronism_type_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2688</th>\n",
       "      <td>zr5654_10_S6</td>\n",
       "      <td>chr5</td>\n",
       "      <td>53094195</td>\n",
       "      <td>53094196</td>\n",
       "      <td>A</td>\n",
       "      <td>[AATTATATAAACAACTTTGTAGGACT]</td>\n",
       "      <td>[(CSQ, ATTATATAAACAACTTTGTAGGACT|3_prime_UTR_v...</td>\n",
       "      <td>Uncertain_significance</td>\n",
       "      <td>ITGA2</td>\n",
       "      <td>Platelet-type_bleeding_disorder_9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2689</th>\n",
       "      <td>zr5654_18_S10</td>\n",
       "      <td>chr5</td>\n",
       "      <td>53094195</td>\n",
       "      <td>53094196</td>\n",
       "      <td>A</td>\n",
       "      <td>[AATTATATAAACAACTTTGTAGGACT]</td>\n",
       "      <td>[(CSQ, ATTATATAAACAACTTTGTAGGACT|3_prime_UTR_v...</td>\n",
       "      <td>Uncertain_significance</td>\n",
       "      <td>ITGA2</td>\n",
       "      <td>Platelet-type_bleeding_disorder_9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2690</th>\n",
       "      <td>zr5654_18_S10</td>\n",
       "      <td>chr22</td>\n",
       "      <td>17112988</td>\n",
       "      <td>17112990</td>\n",
       "      <td>GT</td>\n",
       "      <td>[G]</td>\n",
       "      <td>[(CSQ, -|3_prime_UTR_variant|MODIFIER|IL17RA|E...</td>\n",
       "      <td>Uncertain_significance</td>\n",
       "      <td>IL17RA</td>\n",
       "      <td>Familial_Candidiasis,_Recessive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2691</th>\n",
       "      <td>zr5654_10_S6</td>\n",
       "      <td>chr5</td>\n",
       "      <td>53094195</td>\n",
       "      <td>53094196</td>\n",
       "      <td>A</td>\n",
       "      <td>[AATTATATAAACAACTTTGTAGGACT]</td>\n",
       "      <td>[(CSQ, ATTATATAAACAACTTTGTAGGACT|3_prime_UTR_v...</td>\n",
       "      <td>Uncertain_significance</td>\n",
       "      <td>ITGA2</td>\n",
       "      <td>Platelet-type_bleeding_disorder_9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2692</th>\n",
       "      <td>zr5654_10_S6</td>\n",
       "      <td>chr11</td>\n",
       "      <td>86947200</td>\n",
       "      <td>86947217</td>\n",
       "      <td>TCAAACAAACAAACAAA</td>\n",
       "      <td>[T]</td>\n",
       "      <td>[(CSQ, -|intron_variant&amp;non_coding_transcript_...</td>\n",
       "      <td>Uncertain_significance</td>\n",
       "      <td>FZD4</td>\n",
       "      <td>Familial_exudative_vitreoretinopathy</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2693 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           sampleid contigname      start        end    referenceallele  \\\n",
       "0       zr5654_4_S1      chr16   66508712   66508713                  T   \n",
       "1     zr5654_22_S13      chr17    5028784    5028785                  C   \n",
       "2       zr5654_9_S5      chr16   47700347   47700349                 CA   \n",
       "3      zr5654_10_S6       chr3   49416994   49416995                  G   \n",
       "4       zr5654_7_S3       chr5  137618888  137618891                ATT   \n",
       "...             ...        ...        ...        ...                ...   \n",
       "2688   zr5654_10_S6       chr5   53094195   53094196                  A   \n",
       "2689  zr5654_18_S10       chr5   53094195   53094196                  A   \n",
       "2690  zr5654_18_S10      chr22   17112988   17112990                 GT   \n",
       "2691   zr5654_10_S6       chr5   53094195   53094196                  A   \n",
       "2692   zr5654_10_S6      chr11   86947200   86947217  TCAAACAAACAAACAAA   \n",
       "\n",
       "                  alternatealleles  \\\n",
       "0                              [C]   \n",
       "1                             [CT]   \n",
       "2                              [C]   \n",
       "3                              [A]   \n",
       "4                              [A]   \n",
       "...                            ...   \n",
       "2688  [AATTATATAAACAACTTTGTAGGACT]   \n",
       "2689  [AATTATATAAACAACTTTGTAGGACT]   \n",
       "2690                           [G]   \n",
       "2691  [AATTATATAAACAACTTTGTAGGACT]   \n",
       "2692                           [T]   \n",
       "\n",
       "                                     variant_attributes  \\\n",
       "0     [(CSQ, C|downstream_gene_variant|MODIFIER|TK2|...   \n",
       "1     [(CSQ, T|downstream_gene_variant|MODIFIER|SLC5...   \n",
       "2     [(CSQ, -|3_prime_UTR_variant|MODIFIER|PHKB|ENS...   \n",
       "3     [(CSQ, A|upstream_gene_variant|MODIFIER|RHOA|E...   \n",
       "4     [(CSQ, -|3_prime_UTR_variant|MODIFIER|KLHL3|EN...   \n",
       "...                                                 ...   \n",
       "2688  [(CSQ, ATTATATAAACAACTTTGTAGGACT|3_prime_UTR_v...   \n",
       "2689  [(CSQ, ATTATATAAACAACTTTGTAGGACT|3_prime_UTR_v...   \n",
       "2690  [(CSQ, -|3_prime_UTR_variant|MODIFIER|IL17RA|E...   \n",
       "2691  [(CSQ, ATTATATAAACAACTTTGTAGGACT|3_prime_UTR_v...   \n",
       "2692  [(CSQ, -|intron_variant&non_coding_transcript_...   \n",
       "\n",
       "       clinical_significance    gene  \\\n",
       "0     Uncertain_significance     TK2   \n",
       "1     Uncertain_significance   KIF1C   \n",
       "2     Uncertain_significance    PHKB   \n",
       "3     Uncertain_significance     AMT   \n",
       "4     Uncertain_significance   KLHL3   \n",
       "...                      ...     ...   \n",
       "2688  Uncertain_significance   ITGA2   \n",
       "2689  Uncertain_significance   ITGA2   \n",
       "2690  Uncertain_significance  IL17RA   \n",
       "2691  Uncertain_significance   ITGA2   \n",
       "2692  Uncertain_significance    FZD4   \n",
       "\n",
       "                                               disorder  \n",
       "0     Mitochondrial_DNA_depletion_syndrome,_myopathi...  \n",
       "1                                          not_provided  \n",
       "2              Glycogen_phosphorylase_kinase_deficiency  \n",
       "3                           Non-ketotic_hyperglycinemia  \n",
       "4     Autosomal_dominant_pseudohypoaldosteronism_type_1  \n",
       "...                                                 ...  \n",
       "2688                  Platelet-type_bleeding_disorder_9  \n",
       "2689                  Platelet-type_bleeding_disorder_9  \n",
       "2690                    Familial_Candidiasis,_Recessive  \n",
       "2691                  Platelet-type_bleeding_disorder_9  \n",
       "2692               Familial_exudative_vitreoretinopathy  \n",
       "\n",
       "[2693 rows x 10 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Filter the data to include only Pathogenic and Likely_pathogenic variants, and also filter out all the unknown conditions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_cleaned = df[(df.gene!=\"\") & (df.disorder !=\"not_provided\") & (df.disorder!=\"See_cases\") & (df.clinical_significance != 'Uncertain_significance')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8728681753784)>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ggplot(df_cleaned,aes('disorder')) + geom_bar()+ theme(axis_text_x= element_text(angle=45,vjust=1,hjust=1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's look at conditions that occurred in more than one patient only"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "occurrences = df_cleaned.disorder.value_counts()\n",
    "df_multi_occurrence = df_cleaned[df_cleaned.disorder.isin(occurrences.index[occurrences.gt(1)])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8728680456409)>"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ggplot(df_multi_occurrence,aes(x='gene',y='sampleid',fill='disorder')) + geom_tile()+ theme(axis_text_x= element_text(angle=90,vjust=1,hjust=1))\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us find some information about the demographics of this cohort"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>patient_id</th>\n",
       "      <th>lab_specimen_identifier</th>\n",
       "      <th>sample_type</th>\n",
       "      <th>year_of_birth</th>\n",
       "      <th>reported_gender</th>\n",
       "      <th>state</th>\n",
       "      <th>afr_ancestry_percent</th>\n",
       "      <th>amr_ancestry_percent</th>\n",
       "      <th>eas_ancestry_percent</th>\n",
       "      <th>eur_ancestry_percent</th>\n",
       "      <th>oce_ancestry_percent</th>\n",
       "      <th>sas_ancestry_percent</th>\n",
       "      <th>was_ancestry_percent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1a8b4237-f568-4e82-a190-40da5f1f4b7f</td>\n",
       "      <td>zr5654_18_S10</td>\n",
       "      <td>Anterior_nasal_nares</td>\n",
       "      <td>1979</td>\n",
       "      <td>Female</td>\n",
       "      <td>MD</td>\n",
       "      <td>0.227</td>\n",
       "      <td>0.022</td>\n",
       "      <td>0.561</td>\n",
       "      <td>0.039</td>\n",
       "      <td>0.013</td>\n",
       "      <td>0.096</td>\n",
       "      <td>0.042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>31c58fc7-620a-4288-ad77-d3e64749820b</td>\n",
       "      <td>zr5654_7_S3</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>1978</td>\n",
       "      <td>Female</td>\n",
       "      <td>SC</td>\n",
       "      <td>0.212</td>\n",
       "      <td>0.043</td>\n",
       "      <td>0.475</td>\n",
       "      <td>0.052</td>\n",
       "      <td>0.123</td>\n",
       "      <td>0.094</td>\n",
       "      <td>0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5433a6d8-d6d6-4c88-b3d4-117d64b548cb</td>\n",
       "      <td>zr5654_8_S4</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>2011</td>\n",
       "      <td>Female</td>\n",
       "      <td>SC</td>\n",
       "      <td>0.804</td>\n",
       "      <td>0.010</td>\n",
       "      <td>0.121</td>\n",
       "      <td>0.021</td>\n",
       "      <td>0.004</td>\n",
       "      <td>0.010</td>\n",
       "      <td>0.030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5b1b4d31-c689-4712-87aa-c7a76dd54abe</td>\n",
       "      <td>zr5654_5_S2</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>1954</td>\n",
       "      <td>Female</td>\n",
       "      <td>SC</td>\n",
       "      <td>0.266</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.330</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.390</td>\n",
       "      <td>0.010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6c20fff8-0356-4203-9541-968b406888d1</td>\n",
       "      <td>zr5654_10_S6</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>1967</td>\n",
       "      <td>Female</td>\n",
       "      <td>SC</td>\n",
       "      <td>0.130</td>\n",
       "      <td>0.004</td>\n",
       "      <td>0.085</td>\n",
       "      <td>0.740</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.020</td>\n",
       "      <td>0.020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>768390eb-626b-4021-b36d-30cebc36270e</td>\n",
       "      <td>zr5654_12_S8</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>1977</td>\n",
       "      <td>Female</td>\n",
       "      <td>SC</td>\n",
       "      <td>0.730</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.116</td>\n",
       "      <td>0.093</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.060</td>\n",
       "      <td>0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>aca83995-da9a-4838-aee4-491df647fd1f</td>\n",
       "      <td>zr5654_4_S1</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>1982</td>\n",
       "      <td>Female</td>\n",
       "      <td>SC</td>\n",
       "      <td>0.045</td>\n",
       "      <td>0.072</td>\n",
       "      <td>0.070</td>\n",
       "      <td>0.540</td>\n",
       "      <td>0.005</td>\n",
       "      <td>0.055</td>\n",
       "      <td>0.213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>d4a39e1a-5705-4aed-b99d-0ba6571c3d5d</td>\n",
       "      <td>zr5654_9_S5</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>1955</td>\n",
       "      <td>Female</td>\n",
       "      <td>SC</td>\n",
       "      <td>0.326</td>\n",
       "      <td>0.004</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.560</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.104</td>\n",
       "      <td>0.004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>e7ff2f2b-cf9c-45e3-aaf9-8bd8b660dca9</td>\n",
       "      <td>zr5654_22_S13</td>\n",
       "      <td>Anterior_nasal_nares</td>\n",
       "      <td>1972</td>\n",
       "      <td>Male</td>\n",
       "      <td>WV</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.132</td>\n",
       "      <td>0.040</td>\n",
       "      <td>0.271</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.551</td>\n",
       "      <td>0.002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>ec38ecc6-7487-4677-9e3e-94d1e556239f</td>\n",
       "      <td>zr5654_20_S11</td>\n",
       "      <td>Anterior_nasal_nares</td>\n",
       "      <td>1970</td>\n",
       "      <td>Male</td>\n",
       "      <td>MD</td>\n",
       "      <td>0.040</td>\n",
       "      <td>0.171</td>\n",
       "      <td>0.152</td>\n",
       "      <td>0.283</td>\n",
       "      <td>0.004</td>\n",
       "      <td>0.120</td>\n",
       "      <td>0.230</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             patient_id lab_specimen_identifier  \\\n",
       "0  1a8b4237-f568-4e82-a190-40da5f1f4b7f           zr5654_18_S10   \n",
       "1  31c58fc7-620a-4288-ad77-d3e64749820b             zr5654_7_S3   \n",
       "2  5433a6d8-d6d6-4c88-b3d4-117d64b548cb             zr5654_8_S4   \n",
       "3  5b1b4d31-c689-4712-87aa-c7a76dd54abe             zr5654_5_S2   \n",
       "4  6c20fff8-0356-4203-9541-968b406888d1            zr5654_10_S6   \n",
       "5  768390eb-626b-4021-b36d-30cebc36270e            zr5654_12_S8   \n",
       "6  aca83995-da9a-4838-aee4-491df647fd1f             zr5654_4_S1   \n",
       "7  d4a39e1a-5705-4aed-b99d-0ba6571c3d5d             zr5654_9_S5   \n",
       "8  e7ff2f2b-cf9c-45e3-aaf9-8bd8b660dca9           zr5654_22_S13   \n",
       "9  ec38ecc6-7487-4677-9e3e-94d1e556239f           zr5654_20_S11   \n",
       "\n",
       "            sample_type  year_of_birth reported_gender state  \\\n",
       "0  Anterior_nasal_nares           1979          Female    MD   \n",
       "1               Unknown           1978          Female    SC   \n",
       "2               Unknown           2011          Female    SC   \n",
       "3               Unknown           1954          Female    SC   \n",
       "4               Unknown           1967          Female    SC   \n",
       "5               Unknown           1977          Female    SC   \n",
       "6               Unknown           1982          Female    SC   \n",
       "7               Unknown           1955          Female    SC   \n",
       "8  Anterior_nasal_nares           1972            Male    WV   \n",
       "9  Anterior_nasal_nares           1970            Male    MD   \n",
       "\n",
       "   afr_ancestry_percent  amr_ancestry_percent  eas_ancestry_percent  \\\n",
       "0                 0.227                 0.022                 0.561   \n",
       "1                 0.212                 0.043                 0.475   \n",
       "2                 0.804                 0.010                 0.121   \n",
       "3                 0.266                 0.000                 0.002   \n",
       "4                 0.130                 0.004                 0.085   \n",
       "5                 0.730                 0.000                 0.116   \n",
       "6                 0.045                 0.072                 0.070   \n",
       "7                 0.326                 0.004                 0.001   \n",
       "8                 0.002                 0.132                 0.040   \n",
       "9                 0.040                 0.171                 0.152   \n",
       "\n",
       "   eur_ancestry_percent  oce_ancestry_percent  sas_ancestry_percent  \\\n",
       "0                 0.039                 0.013                 0.096   \n",
       "1                 0.052                 0.123                 0.094   \n",
       "2                 0.021                 0.004                 0.010   \n",
       "3                 0.330                 0.002                 0.390   \n",
       "4                 0.740                 0.001                 0.020   \n",
       "5                 0.093                 0.000                 0.060   \n",
       "6                 0.540                 0.005                 0.055   \n",
       "7                 0.560                 0.001                 0.104   \n",
       "8                 0.271                 0.002                 0.551   \n",
       "9                 0.283                 0.004                 0.120   \n",
       "\n",
       "   was_ancestry_percent  \n",
       "0                 0.042  \n",
       "1                 0.001  \n",
       "2                 0.030  \n",
       "3                 0.010  \n",
       "4                 0.020  \n",
       "5                 0.001  \n",
       "6                 0.213  \n",
       "7                 0.004  \n",
       "8                 0.002  \n",
       "9                 0.230  "
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = wr.athena.read_sql_query(\"SELECT * FROM ovation_clinicogenomics\", database=\"ovation_claims\",workgroup = \"athena3\")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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