From f69b3717e8417466615f99be8d5e7ad7a8a4491c Mon Sep 17 00:00:00 2001
From: QuiltSimon <simon@quiltdata.io>
Date: Mon, 3 Jun 2024 14:48:18 -0500
Subject: [PATCH] Recommending code changes to enable notebook to work out of
 the box

---
 ...ery_athena_data_and_perform_analysis.ipynb | 329 ++++++++++--------
 1 file changed, 182 insertions(+), 147 deletions(-)

diff --git a/05_query_athena_data_and_perform_analysis.ipynb b/05_query_athena_data_and_perform_analysis.ipynb
index 9013a4e..4989504 100644
--- a/05_query_athena_data_and_perform_analysis.ipynb
+++ b/05_query_athena_data_and_perform_analysis.ipynb
@@ -2,7 +2,9 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "source": [
     "# Tutorial 5: Query metadata & pipeline outputs in Athena to accelerate analysis\n",
     "\n",
@@ -17,15 +19,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
+   "execution_count": 14,
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "import sqlalchemy\n",
     "from pyathena import connect\n",
     "import pandas as pd\n",
     "import matplotlib.pyplot as plt\n",
-    "import seaborn as sns"
+    "import seaborn as sns\n",
+    "import json"
    ]
   },
   {
@@ -37,21 +42,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
+   "execution_count": 4,
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "# user to fill in AWS credentials (or auth in preferred method)\n",
-    "aws_access_key_id = \"USER_ACCESS KEY\"\n",
-    "aws_secret_access_key = \"USER SECRET ACCESS KEY\"\n",
+    "aws_access_key_id = \"Access_Key\"\n",
+    "aws_secret_access_key = \"Secret_Access_Key\"\n",
     "region_name = \"us-east-1\"\n",
     "bucket_name = \"s3://quilt-example-bucket/ccle\""
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
+   "execution_count": 5,
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "# connect to Athena\n",
@@ -97,14 +106,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
-   "metadata": {},
+   "execution_count": 6,
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/var/folders/np/3pjq4pjd4gj2x_kjmxbt2wxc0000gn/T/ipykernel_87390/1304740185.py:21: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n",
+      "/tmp/ipykernel_15668/1304740185.py:21: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n",
       "  egfr_expression = pd.read_sql(query_1, conn)\n"
      ]
     },
@@ -157,121 +168,121 @@
        "      <th>0</th>\n",
        "      <td>NM_201284.1</td>\n",
        "      <td>2865</td>\n",
-       "      <td>2627.219</td>\n",
+       "      <td>2648.473</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000</td>\n",
        "      <td>20190225_PRJNA523380_nfcore_rnaseq</td>\n",
-       "      <td>SRR8618316</td>\n",
-       "      <td>ccle/20190225_PRJNA523380_SRR8618316</td>\n",
-       "      <td>fd5b754de3883726f70ba0c60cef0d58cda93223b5d980...</td>\n",
+       "      <td>SRR8618318</td>\n",
+       "      <td>ccle/20190225_PRJNA523380_SRR8618318</td>\n",
+       "      <td>c77502c1daa6a66c4445c15df0519b73776f1c1352c1ba...</td>\n",
        "      <td>latest</td>\n",
        "      <td>...</td>\n",
-       "      <td>WM1799_SKIN</td>\n",
-       "      <td>Unknown</td>\n",
-       "      <td>WISTAR</td>\n",
+       "      <td>WM115_SKIN</td>\n",
+       "      <td>female</td>\n",
+       "      <td>None</td>\n",
        "      <td>TRANSCRIPTOMIC</td>\n",
        "      <td>cDNA</td>\n",
        "      <td>PRJNA523380</td>\n",
-       "      <td>RNASeq-WM1799_SKIN</td>\n",
+       "      <td>RNASeq-WM115_SKIN</td>\n",
        "      <td>cell culture</td>\n",
-       "      <td>349.0</td>\n",
-       "      <td>None</td>\n",
+       "      <td>384.0</td>\n",
+       "      <td>59.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>NM_201284.1</td>\n",
        "      <td>2865</td>\n",
-       "      <td>2643.287</td>\n",
-       "      <td>0.487383</td>\n",
-       "      <td>5.905</td>\n",
+       "      <td>2633.750</td>\n",
+       "      <td>0.295669</td>\n",
+       "      <td>3.321</td>\n",
        "      <td>20190225_PRJNA523380_nfcore_rnaseq</td>\n",
-       "      <td>SRR8618309</td>\n",
-       "      <td>ccle/20190225_PRJNA523380_SRR8618309</td>\n",
-       "      <td>462d12730869d2d14d6c9468b0ea0b887623fe542b5b62...</td>\n",
+       "      <td>SRR8618308</td>\n",
+       "      <td>ccle/20190225_PRJNA523380_SRR8618308</td>\n",
+       "      <td>5b99a133fad51ad8f4116fb38a5da222b57e5ab4062aa5...</td>\n",
        "      <td>latest</td>\n",
        "      <td>...</td>\n",
-       "      <td>YD10B_UPPER_AERODIGESTIVE_TRACT</td>\n",
+       "      <td>YD15_SALIVARY_GLAND</td>\n",
        "      <td>male</td>\n",
        "      <td>KCLB</td>\n",
        "      <td>TRANSCRIPTOMIC</td>\n",
        "      <td>cDNA</td>\n",
        "      <td>PRJNA523380</td>\n",
-       "      <td>RNASeq-YD10B_UPPER_AERODIGESTIVE_TRACT</td>\n",
+       "      <td>RNASeq-YD15_SALIVARY_GLAND</td>\n",
        "      <td>cell culture</td>\n",
-       "      <td>323.0</td>\n",
-       "      <td>67.0</td>\n",
+       "      <td>180.0</td>\n",
+       "      <td>39.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>NM_201284.1</td>\n",
        "      <td>2865</td>\n",
-       "      <td>2638.196</td>\n",
-       "      <td>0.175977</td>\n",
-       "      <td>13.426</td>\n",
+       "      <td>2658.873</td>\n",
+       "      <td>0.014337</td>\n",
+       "      <td>1.339</td>\n",
        "      <td>20190224_PRJNA523380_nfcore_rnaseq</td>\n",
-       "      <td>SRR8615906</td>\n",
-       "      <td>ccle/20190224_PRJNA523380_SRR8615906</td>\n",
-       "      <td>87c5c3af65597a0d4c6b1a8a8607f5e4029495a7a43e6f...</td>\n",
+       "      <td>SRR8616180</td>\n",
+       "      <td>ccle/20190224_PRJNA523380_SRR8616180</td>\n",
+       "      <td>5e2c55d774bb7a2e52ef614718121635ea5d358427157c...</td>\n",
        "      <td>latest</td>\n",
        "      <td>...</td>\n",
-       "      <td>KM12_LARGE_INTESTINE</td>\n",
-       "      <td>Unknown</td>\n",
-       "      <td>NIBRI</td>\n",
+       "      <td>HCC1500_BREAST</td>\n",
+       "      <td>female</td>\n",
+       "      <td>ATCC</td>\n",
        "      <td>TRANSCRIPTOMIC</td>\n",
        "      <td>cDNA</td>\n",
        "      <td>PRJNA523380</td>\n",
-       "      <td>RNASeq-KM12_LARGE_INTESTINE</td>\n",
+       "      <td>RNASeq-HCC1500_BREAST</td>\n",
        "      <td>cell culture</td>\n",
-       "      <td>3296.0</td>\n",
-       "      <td>None</td>\n",
+       "      <td>211.0</td>\n",
+       "      <td>32.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>NM_201284.1</td>\n",
        "      <td>2865</td>\n",
-       "      <td>2591.898</td>\n",
-       "      <td>0.016812</td>\n",
-       "      <td>1.567</td>\n",
+       "      <td>2640.989</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>20190225_PRJNA523380_nfcore_rnaseq</td>\n",
-       "      <td>SRR8618305</td>\n",
-       "      <td>ccle/20190225_PRJNA523380_SRR8618305</td>\n",
-       "      <td>87f90a5a8c29f600a905165e96739fd74864f969950d76...</td>\n",
+       "      <td>SRR8618307</td>\n",
+       "      <td>ccle/20190225_PRJNA523380_SRR8618307</td>\n",
+       "      <td>586d59d31b8fd270f3ed982ed099008da6382ef772c48c...</td>\n",
        "      <td>latest</td>\n",
        "      <td>...</td>\n",
-       "      <td>VCAP_PROSTATE</td>\n",
+       "      <td>WSUDLCL2_HAEMATOPOIETIC_AND_LYMPHOID_TISSUE</td>\n",
        "      <td>male</td>\n",
-       "      <td>ATCC</td>\n",
+       "      <td>DSMZ</td>\n",
        "      <td>TRANSCRIPTOMIC</td>\n",
        "      <td>cDNA</td>\n",
        "      <td>PRJNA523380</td>\n",
-       "      <td>RNASeq-VCAP_PROSTATE</td>\n",
+       "      <td>RNASeq-WSUDLCL2_HAEMATOPOIETIC_AND_LYMPHOID_TI...</td>\n",
        "      <td>cell culture</td>\n",
-       "      <td>158.0</td>\n",
-       "      <td>59.0</td>\n",
+       "      <td>231.0</td>\n",
+       "      <td>41.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>NM_201284.1</td>\n",
        "      <td>2865</td>\n",
-       "      <td>2640.313</td>\n",
-       "      <td>0.024008</td>\n",
-       "      <td>1.681</td>\n",
-       "      <td>20190223_PRJNA523380_nfcore_rnaseq</td>\n",
-       "      <td>SRR8615493</td>\n",
-       "      <td>ccle/20190223_PRJNA523380_SRR8615493</td>\n",
-       "      <td>628fae032ee78f5b88b7e4e35ee4cbb7b634930cd20d94...</td>\n",
+       "      <td>2631.873</td>\n",
+       "      <td>0.355751</td>\n",
+       "      <td>7.532</td>\n",
+       "      <td>20190225_PRJNA523380_nfcore_rnaseq</td>\n",
+       "      <td>SRR8618306</td>\n",
+       "      <td>ccle/20190225_PRJNA523380_SRR8618306</td>\n",
+       "      <td>ba17534efac128612d76a085e3fa02365a42ebed0137fc...</td>\n",
        "      <td>latest</td>\n",
        "      <td>...</td>\n",
-       "      <td>ISHIKAWAHERAKLIO02ER_ENDOMETRIUM</td>\n",
-       "      <td>female</td>\n",
-       "      <td>None</td>\n",
+       "      <td>YAPC_PANCREAS</td>\n",
+       "      <td>male</td>\n",
+       "      <td>DSMZ</td>\n",
        "      <td>TRANSCRIPTOMIC</td>\n",
        "      <td>cDNA</td>\n",
        "      <td>PRJNA523380</td>\n",
-       "      <td>RNASeq-ISHIKAWAHERAKLIO02ER_ENDOMETRIUM</td>\n",
+       "      <td>RNASeq-YAPC_PANCREAS</td>\n",
        "      <td>cell culture</td>\n",
-       "      <td>2745.0</td>\n",
-       "      <td>39.0</td>\n",
+       "      <td>229.0</td>\n",
+       "      <td>43.0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -280,58 +291,65 @@
       ],
       "text/plain": [
        "          name length effectivelength       tpm numreads  \\\n",
-       "0  NM_201284.1   2865        2627.219  0.000000    0.000   \n",
-       "1  NM_201284.1   2865        2643.287  0.487383    5.905   \n",
-       "2  NM_201284.1   2865        2638.196  0.175977   13.426   \n",
-       "3  NM_201284.1   2865        2591.898  0.016812    1.567   \n",
-       "4  NM_201284.1   2865        2640.313  0.024008    1.681   \n",
+       "0  NM_201284.1   2865        2648.473  0.000000    0.000   \n",
+       "1  NM_201284.1   2865        2633.750  0.295669    3.321   \n",
+       "2  NM_201284.1   2865        2658.873  0.014337    1.339   \n",
+       "3  NM_201284.1   2865        2640.989  0.000000    0.000   \n",
+       "4  NM_201284.1   2865        2631.873  0.355751    7.532   \n",
        "\n",
        "                               run_id   sample_id  \\\n",
-       "0  20190225_PRJNA523380_nfcore_rnaseq  SRR8618316   \n",
-       "1  20190225_PRJNA523380_nfcore_rnaseq  SRR8618309   \n",
-       "2  20190224_PRJNA523380_nfcore_rnaseq  SRR8615906   \n",
-       "3  20190225_PRJNA523380_nfcore_rnaseq  SRR8618305   \n",
-       "4  20190223_PRJNA523380_nfcore_rnaseq  SRR8615493   \n",
+       "0  20190225_PRJNA523380_nfcore_rnaseq  SRR8618318   \n",
+       "1  20190225_PRJNA523380_nfcore_rnaseq  SRR8618308   \n",
+       "2  20190224_PRJNA523380_nfcore_rnaseq  SRR8616180   \n",
+       "3  20190225_PRJNA523380_nfcore_rnaseq  SRR8618307   \n",
+       "4  20190225_PRJNA523380_nfcore_rnaseq  SRR8618306   \n",
        "\n",
        "                               pkg_name  \\\n",
-       "0  ccle/20190225_PRJNA523380_SRR8618316   \n",
-       "1  ccle/20190225_PRJNA523380_SRR8618309   \n",
-       "2  ccle/20190224_PRJNA523380_SRR8615906   \n",
-       "3  ccle/20190225_PRJNA523380_SRR8618305   \n",
-       "4  ccle/20190223_PRJNA523380_SRR8615493   \n",
+       "0  ccle/20190225_PRJNA523380_SRR8618318   \n",
+       "1  ccle/20190225_PRJNA523380_SRR8618308   \n",
+       "2  ccle/20190224_PRJNA523380_SRR8616180   \n",
+       "3  ccle/20190225_PRJNA523380_SRR8618307   \n",
+       "4  ccle/20190225_PRJNA523380_SRR8618306   \n",
        "\n",
        "                                            top_hash timestamp  ...  \\\n",
-       "0  fd5b754de3883726f70ba0c60cef0d58cda93223b5d980...    latest  ...   \n",
-       "1  462d12730869d2d14d6c9468b0ea0b887623fe542b5b62...    latest  ...   \n",
-       "2  87c5c3af65597a0d4c6b1a8a8607f5e4029495a7a43e6f...    latest  ...   \n",
-       "3  87f90a5a8c29f600a905165e96739fd74864f969950d76...    latest  ...   \n",
-       "4  628fae032ee78f5b88b7e4e35ee4cbb7b634930cd20d94...    latest  ...   \n",
+       "0  c77502c1daa6a66c4445c15df0519b73776f1c1352c1ba...    latest  ...   \n",
+       "1  5b99a133fad51ad8f4116fb38a5da222b57e5ab4062aa5...    latest  ...   \n",
+       "2  5e2c55d774bb7a2e52ef614718121635ea5d358427157c...    latest  ...   \n",
+       "3  586d59d31b8fd270f3ed982ed099008da6382ef772c48c...    latest  ...   \n",
+       "4  ba17534efac128612d76a085e3fa02365a42ebed0137fc...    latest  ...   \n",
+       "\n",
+       "                                     patientid     sex celllinesource  \\\n",
+       "0                                   WM115_SKIN  female           None   \n",
+       "1                          YD15_SALIVARY_GLAND    male           KCLB   \n",
+       "2                               HCC1500_BREAST  female           ATCC   \n",
+       "3  WSUDLCL2_HAEMATOPOIETIC_AND_LYMPHOID_TISSUE    male           DSMZ   \n",
+       "4                                YAPC_PANCREAS    male           DSMZ   \n",
        "\n",
-       "                          patientid      sex celllinesource   librarysource  \\\n",
-       "0                       WM1799_SKIN  Unknown         WISTAR  TRANSCRIPTOMIC   \n",
-       "1   YD10B_UPPER_AERODIGESTIVE_TRACT     male           KCLB  TRANSCRIPTOMIC   \n",
-       "2              KM12_LARGE_INTESTINE  Unknown          NIBRI  TRANSCRIPTOMIC   \n",
-       "3                     VCAP_PROSTATE     male           ATCC  TRANSCRIPTOMIC   \n",
-       "4  ISHIKAWAHERAKLIO02ER_ENDOMETRIUM   female           None  TRANSCRIPTOMIC   \n",
+       "    librarysource libraryselection   bioproject  \\\n",
+       "0  TRANSCRIPTOMIC             cDNA  PRJNA523380   \n",
+       "1  TRANSCRIPTOMIC             cDNA  PRJNA523380   \n",
+       "2  TRANSCRIPTOMIC             cDNA  PRJNA523380   \n",
+       "3  TRANSCRIPTOMIC             cDNA  PRJNA523380   \n",
+       "4  TRANSCRIPTOMIC             cDNA  PRJNA523380   \n",
        "\n",
-       "  libraryselection   bioproject                              libraryname  \\\n",
-       "0             cDNA  PRJNA523380                       RNASeq-WM1799_SKIN   \n",
-       "1             cDNA  PRJNA523380   RNASeq-YD10B_UPPER_AERODIGESTIVE_TRACT   \n",
-       "2             cDNA  PRJNA523380              RNASeq-KM12_LARGE_INTESTINE   \n",
-       "3             cDNA  PRJNA523380                     RNASeq-VCAP_PROSTATE   \n",
-       "4             cDNA  PRJNA523380  RNASeq-ISHIKAWAHERAKLIO02ER_ENDOMETRIUM   \n",
+       "                                         libraryname    sampletype  \\\n",
+       "0                                  RNASeq-WM115_SKIN  cell culture   \n",
+       "1                         RNASeq-YD15_SALIVARY_GLAND  cell culture   \n",
+       "2                              RNASeq-HCC1500_BREAST  cell culture   \n",
+       "3  RNASeq-WSUDLCL2_HAEMATOPOIETIC_AND_LYMPHOID_TI...  cell culture   \n",
+       "4                               RNASeq-YAPC_PANCREAS  cell culture   \n",
        "\n",
-       "     sampletype mutationcount   age  \n",
-       "0  cell culture         349.0  None  \n",
-       "1  cell culture         323.0  67.0  \n",
-       "2  cell culture        3296.0  None  \n",
-       "3  cell culture         158.0  59.0  \n",
-       "4  cell culture        2745.0  39.0  \n",
+       "  mutationcount   age  \n",
+       "0         384.0  59.0  \n",
+       "1         180.0  39.0  \n",
+       "2         211.0  32.0  \n",
+       "3         231.0  41.0  \n",
+       "4         229.0  43.0  \n",
        "\n",
        "[5 rows x 80 columns]"
       ]
      },
-     "execution_count": 55,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -363,12 +381,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
-   "metadata": {},
+   "execution_count": 7,
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -407,14 +427,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
-   "metadata": {},
+   "execution_count": 8,
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/var/folders/np/3pjq4pjd4gj2x_kjmxbt2wxc0000gn/T/ipykernel_87390/2537690394.py:20: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n",
+      "/tmp/ipykernel_15668/2537690394.py:20: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n",
       "  liver_cell_lines = pd.read_sql(query_2, conn)\n"
      ]
     },
@@ -482,7 +504,7 @@
        "2            JHH-5  SRR8615920   liver    JHH5_LIVER  male"
       ]
      },
-     "execution_count": 61,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -526,14 +548,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 93,
-   "metadata": {},
+   "execution_count": 15,
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/var/folders/np/3pjq4pjd4gj2x_kjmxbt2wxc0000gn/T/ipykernel_87390/1916184992.py:19: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n",
+      "/tmp/ipykernel_15668/211798334.py:19: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n",
       "  pipeline_metadata = pd.read_sql(query_3, conn)\n"
      ]
     },
@@ -568,18 +592,18 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
-       "      <td>ccle/20190225_PRJNA523380_nfcore_rnaseq</td>\n",
-       "      <td>0d3bb82e640ce25af86a37fa246193b32dab19c9b1e25a...</td>\n",
+       "      <td>ccle/20190224_PRJNA523380_nfcore_rnaseq</td>\n",
+       "      <td>824f2f3d60535cf02146e93ffd80b57d7c40fb0ee88345...</td>\n",
        "      <td>latest</td>\n",
-       "      <td>delete old dirs</td>\n",
+       "      <td>SK: Beautifying again</td>\n",
        "      <td>{\"quilt\":{\"package_id\":\"QuiltPackage.quilt_exa...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td>ccle/20190224_PRJNA523380_nfcore_rnaseq</td>\n",
-       "      <td>158cbcd6746a8c663b302943ebfd60d3211c1c11c390be...</td>\n",
+       "      <td>ccle/20190225_PRJNA523380_nfcore_rnaseq</td>\n",
+       "      <td>0d3bb82e640ce25af86a37fa246193b32dab19c9b1e25a...</td>\n",
        "      <td>latest</td>\n",
-       "      <td>nf-quilt:2024-04-02-boring_joliot: nextflow ru...</td>\n",
+       "      <td>delete old dirs</td>\n",
        "      <td>{\"quilt\":{\"package_id\":\"QuiltPackage.quilt_exa...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
@@ -596,18 +620,18 @@
       ],
       "text/plain": [
        "                                  pkg_name  \\\n",
-       "0  ccle/20190225_PRJNA523380_nfcore_rnaseq   \n",
-       "1  ccle/20190224_PRJNA523380_nfcore_rnaseq   \n",
+       "0  ccle/20190224_PRJNA523380_nfcore_rnaseq   \n",
+       "1  ccle/20190225_PRJNA523380_nfcore_rnaseq   \n",
        "2  ccle/20190223_PRJNA523380_nfcore_rnaseq   \n",
        "\n",
        "                                            top_hash timestamp  \\\n",
-       "0  0d3bb82e640ce25af86a37fa246193b32dab19c9b1e25a...    latest   \n",
-       "1  158cbcd6746a8c663b302943ebfd60d3211c1c11c390be...    latest   \n",
+       "0  824f2f3d60535cf02146e93ffd80b57d7c40fb0ee88345...    latest   \n",
+       "1  0d3bb82e640ce25af86a37fa246193b32dab19c9b1e25a...    latest   \n",
        "2  4539bd0e6603db80fa26a29b7a05ccca81bae6c46857b1...    latest   \n",
        "\n",
        "                                             message  \\\n",
-       "0                                    delete old dirs   \n",
-       "1  nf-quilt:2024-04-02-boring_joliot: nextflow ru...   \n",
+       "0                              SK: Beautifying again   \n",
+       "1                                    delete old dirs   \n",
        "2  nf-quilt:2024-03-10-trusting_blackwell: nextfl...   \n",
        "\n",
        "                                           user_meta  \n",
@@ -616,7 +640,7 @@
        "2  {\"quilt\":{\"package_id\":\"QuiltPackage.quilt_exa...  "
       ]
      },
-     "execution_count": 93,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -634,7 +658,7 @@
     "\n",
     "# Execute the query\n",
     "cursor = conn.cursor()\n",
-    "cursor.execute(query)\n",
+    "cursor.execute(query_3)\n",
     "\n",
     "# Fetch the results\n",
     "results = cursor.fetchall()\n",
@@ -646,8 +670,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 94,
-   "metadata": {},
+   "execution_count": 17,
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "data": {
@@ -655,20 +681,22 @@
        "'3.14.0'"
       ]
      },
-     "execution_count": 94,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "# parse metadata to find pipeline version\n",
-    "json.loads(pkg_metadata[\"user_meta\"][0])[\"workflow\"][\"manifest\"][\"values\"][0][\"version\"]"
+    "json.loads(pipeline_metadata[\"user_meta\"][0])[\"workflow\"][\"manifest\"][\"values\"][0][\"version\"]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 95,
-   "metadata": {},
+   "execution_count": 19,
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "data": {
@@ -676,7 +704,7 @@
        "{'remove_ribo_rna': False,\n",
        " 'custom_config_base': 'https://raw.githubusercontent.com/nf-core/configs/master',\n",
        " 'umi_discard_read': 'null',\n",
-       " 'gencode': False,\n",
+       " 'gencode': True,\n",
        " 'monochrome-logs': False,\n",
        " 'plaintext_email': False,\n",
        " 'validations3pathcheck': False,\n",
@@ -702,7 +730,7 @@
        " 'skip_qc': False,\n",
        " 'version': False,\n",
        " 'publish_dir_mode': 'copy',\n",
-       " 'input': 's3://quilt-example-bucket/ccle/20190225_PRJNA523380_nfcore_rnaseq/20190225_PRJNA523380__samplesheet.csv',\n",
+       " 'input': 's3://quilt-example-bucket/ccle/20190224_PRJNA523380_nfcore_rnaseq/20190224_PRJNA523380__samplesheet.csv',\n",
        " 'bbsplit_fasta_list': 'null',\n",
        " 'skip_bigwig': False,\n",
        " 'config_profile_name': 'null',\n",
@@ -718,7 +746,7 @@
        " 'skip_qualimap': False,\n",
        " 'star_index': 's3://ngi-igenomes/igenomes/Homo_sapiens/NCBI/GRCh38/Sequence/STARIndex/',\n",
        " 'skip_stringtie': False,\n",
-       " 'gtf_extra_attributes': 'gene_name',\n",
+       " 'gtf_extra_attributes': 'gene_name,gene_id',\n",
        " 'extra_kallisto_quant_args': 'null',\n",
        " 'transcript_fasta': 'null',\n",
        " 'hisat2_index': 'null',\n",
@@ -733,7 +761,7 @@
        " 'kallisto_quant_fraglen': '200',\n",
        " 'extra_salmon_quant_args': 'null',\n",
        " 'skip_pseudo_alignment': False,\n",
-       " 'outdir': 'quilt+s3://quilt-example-bucket#package=ccle/20190225_PRJNA523380_nfcore_rnaseq',\n",
+       " 'outdir': 'quilt+s3://quilt-example-bucket#package=ccle/20190224_PRJNA523380_nfcore_rnaseq',\n",
        " 'help': False,\n",
        " 'genome': 'GRCh38',\n",
        " 'umitools_grouping_method': 'directional',\n",
@@ -795,7 +823,7 @@
        " 'salmon_index': 'null'}"
       ]
      },
-     "execution_count": 95,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -803,13 +831,20 @@
    "source": [
     "# lots of other useful metadata appended by nf-quilt as well\n",
     "# including all pipeline params\n",
-    "json.loads(pkg_metadata[\"user_meta\"][0])[\"params\"]"
+    "json.loads(pipeline_metadata[\"user_meta\"][0])[\"params\"]"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "base",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -823,9 +858,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.5"
+   "version": "3.10.8"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }