Changed the format of submodule 00

Author: hadiparsianNIH

GoogleCloud/Submodule_00_background.ipynb

@@ -14,7 +14,7 @@
    "id": "5e6d2086-4dbf-4a61-a5bb-8f08a269f3fa",
    "metadata": {},
    "source": [
-    "## Welcome!\n",
+    "## Overview\n",
     "\n",
     "This is a series of notebooks that allows you to explore the biological and computational process of the transcriptome assembly. Through these notebooks, you will also learn to leverage the powerful capabilities of tools such as Nextflow and Google Life Science API to bring your computational capabilities to the next level!\n",
     "\n",
@@ -25,6 +25,40 @@
     "Good luck, and have fun!"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "3518c1a9",
+   "metadata": {},
+   "source": [
+    "## Learning Objectives:\n",
+    "\n",
+    "1. **Assess prior knowledge:**  A pre-check quiz verifies foundational understanding of DNA, RNA, transcription, and gene expression.\n",
+    "\n",
+    "2. **Introduce transcriptome assembly:** Learners gain an understanding of what transcriptome assembly is, why RNA sequencing is performed, and the overall workflow involved.\n",
+    "\n",
+    "3. **Explain the process of transcriptome assembly:** This includes understanding preprocessing, sequence assembly using de Bruijn graphs, assembly assessment (internal and external consistency, BUSCO), and refinement techniques.\n",
+    "\n",
+    "4. **Introduce workflow management:** Learners are introduced to the concept of workflows/pipelines in bioinformatics and the role of workflow management systems like Nextflow.\n",
+    "\n",
+    "5. **Explain the use of Docker containers:** The notebook explains the purpose and benefits of using Docker containers for managing software dependencies in bioinformatics.\n",
+    "\n",
+    "6. **Introduce the Google Cloud Life Sciences API:** Learners are introduced to the Google Cloud Life Sciences API and its advantages for managing and executing workflows on cloud computing resources.\n",
+    "\n",
+    "7. **Familiarize learners with Jupyter Notebooks:** The notebook provides instructions on how to navigate and use Jupyter Notebooks, including cell types and execution order."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6a23eec6",
+   "metadata": {},
+   "source": [
+    "## Prerequisites\n",
+    "\n",
+    "* **Basic Biology Knowledge:**  A foundational understanding of DNA, RNA, transcription, and gene expression is assumed.  The notebook includes quizzes to assess this knowledge.\n",
+    "* **Python Programming:** While the notebook itself doesn't contain complex Python code, familiarity with Python syntax and the Jupyter Notebook environment is helpful.\n",
+    "* **Command Line Interface (CLI) Familiarity:** The notebook mentions using `pip` (a command-line package installer), indicating some CLI knowledge is beneficial, although not strictly required for completing the quizzes and reviewing the material."
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "22b95a28-fad7-4b6c-99ae-093c323f769c",
@@ -383,14 +417,30 @@
   },
   {
    "cell_type": "markdown",
-   "id": "489beca6-4a9e-4a2e-a646-6b276270d810",
+   "id": "8d3cf5c9",
+   "metadata": {},
+   "source": [
+    "## Conclusion\n",
+    "\n",
+    "This introductory Jupyter Notebook provided essential background information and a pre-requisite knowledge check on fundamental molecular biology concepts (DNA, RNA, transcription, gene expression) crucial for understanding transcriptome assembly. The notebook established the context for the subsequent modules, outlining the workflow involving RNA-seq data, transcriptome assembly techniques (including de Bruijn graphs, BUSCO analysis), and the use of Nextflow and Google Cloud Life Sciences API for efficient workflow execution and management. The inclusion of interactive quizzes and video resources enhanced learning and engagement, preparing learners for the practical applications and computational challenges presented in the following notebooks. Successful completion of the checkpoint quizzes demonstrates readiness to proceed to the next stage of the MDIBL Transcriptome Assembly Learning Module."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "421cebc3",
    "metadata": {},
    "source": [
-    "## When you are ready, proceed to the next notebook: [`Submodule_01_prog_setup.ipynb`](./Submodule_01_prog_setup.ipynb)."
+    "## Clean Up\n",
+    "\n",
+    "Remember to proceed to the next notebook [`Submodule_01_prog_setup.ipynb`](./Submodule_01_prog_setup.ipynb) or shut down your instance if you are finished."
    ]
   }
  ],
- "metadata": {},
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
  "nbformat": 4,
  "nbformat_minor": 5
 }

test.md

@@ -0,0 +1,30 @@
+This Jupyter notebook is an introductory module for a transcriptome assembly learning course.  Here's a breakdown of its prerequisites, API requirements, and cloud access needs:
+
+**Prerequisites:**
+
+* **Basic Biology Knowledge:**  A foundational understanding of DNA, RNA, transcription, and gene expression is assumed.  The notebook includes quizzes to assess this knowledge.
+* **Python Programming:** While the notebook itself doesn't contain complex Python code, familiarity with Python syntax and the Jupyter Notebook environment is helpful.
+* **Command Line Interface (CLI) Familiarity:** The notebook mentions using `pip` (a command-line package installer), indicating some CLI knowledge is beneficial, although not strictly required for completing the quizzes and reviewing the material.
+
+
+**APIs:**
+
+* **No APIs are directly used in this introductory notebook.**  The notebook *mentions* the Google Cloud Life Sciences API as a tool that will be used in later modules, but it's not utilized within this specific file.
+
+
+**Cloud Platform Account Roles and Access:**
+
+* **None required for this notebook.**  The Google Cloud Life Sciences API is mentioned for later modules, implying that access to a Google Cloud Platform account with appropriate permissions will be needed later, but this introductory notebook only requires local execution and doesn't necessitate any cloud interaction.
+
+
+**Necessary Cloud Platform Access:**
+
+* **None for this notebook.**  This notebook focuses on background information and introductory concepts. Cloud access would be required for later parts of the course, based on its reference to Google Cloud Life Sciences API, but not for this particular Jupyter notebook.
+
+**Software Installations (mentioned in notebook):**
+
+* `jupyterquiz==2.0.7` (for the quizzes)
+* `jupytercards` (also for quizzes, though not used in this specific notebook)
+
+
+In summary, this notebook is a self-contained introductory lesson.  While future modules will require cloud access and specific APIs, this particular file only requires basic biological knowledge, familiarity with Python and Jupyter, and installation of a couple of Python packages.