The INCLUDE Data Hub is a new resource that securely hosts human clinical, genomic, transcriptomic, proteomic, and other data providing a wealth of opportunities to study conditions that affect individuals with Down syndrome. Today, the approach to answering new scientific questions with these data often uses cloud-based methods accessible through web browsers.

During a three-hour virtual training, users learn the know-how to ask scientific questions with these data using cloud platforms and workflows. Users will learn how to build and share processes that assure reproducibility, repurposablility regardless of the computational environment. While many things are possible, the user will be oriented to approaching their work in a modular, testable fashion.

If you have not already done so, please go ahead and create an account on CAVATICA

For today's class, if you have not already done so, let my colleagues know so we can add you to the appropriate billing group.

• Step-by-Step Instructions to log into CAVATICA and Start a Notebook

• Log into INCLUDE Data Hub

• Log into CAVATICA from INCLUDE Data Hub.

• Start a DataCruncher Notebook

While things start to cook -- let me review the Agenda and show a brief presentation

Time (UTC)	Programme
11.00 - 11.10	Welcome Address and Presentation of Tutorial Agenda
11.10 - 11.15	0. A few simple rules for easier workflow maintenance and reuse
11.15 - 11.30	1. Example Volcano Plot on CAVATICA
11:30 - 11.40	2. Creating a conda environment
11:40 - 11:50	3. Building Dockerfiles
11:50 - 12:20	4. Building A Nextflow Script
12:20 - 12:30	5. Building A CWL Script
12.30 - 12.45	☕ Short break - Stretch your legs! (15 minutes) ☕
12.45 - 13.00	6. Shared elements across workflow languages
13.00 - 13.30	7. Working with Apps on the CAVATICA
13:30 - 13.40	8. GitHub Actions to build, test and deposit container images
13:40 - 13.50	9. A Published Example: Zenodo
13.50 - 14.00	Closing remarks and future directions

Anaconda Package Jupytext	CAVATICA Create Developer Token	CAVATICA Add samtools to Docker Repository	Conda Create env and install GitHub CLI
CAVATICA DataCruncher JupyterLab Startup	Generate GitHub Personal Access Tokens	GitHub Auth Login	GitHub Clone FHIR Exercises
INCLUDE DataHub Login with ORCID	CAVATICA Login	GitHub Actions with STAR	Anaconda Search GitHub CLI
Shell Google Cloud

In a short 3 hour course, the learner learned elements of style in the construction and containerization of small single-function processes that facilitate repurposable workflow creation and execution. This hands-on-tutorial was given through a webinar with the to coincide with the launch of the INCLUDE Data Hub. This repository was used in the course and contains self-learnings to facilitate work. In this repository, contains how these processes may be kept up-to-date and alert the creator to the functional state of these processes (working or failing) by using a feature found within GitHub called GitHub Actions. This hands-on-course will use a small example to provide the structure, philosophy and approach to achieving this desirable outcome. This course seeks to help to demystify and make accessible powerful methods one can use to achieve platform independence and platform interoperability. Using a simple example to demonstrate these techniques, we will break down and walk the learner through each of the construction steps. The learners will be introduced to Conda, Docker, GitHub and the standard workflow language, Nextflow. If time permits, we will also show how these containerized processes can also be represented in a second standard workflow language implementation (e.g. Common Workflow Language or WDL). By the end of the course, the learner will understand these Elements of Style and will know how Conda, Docker, GitHub, Zenodo, and Nextflow enable repurposable research. Moreover, these steps will be on GitHub for the Learner to return to and reproduce themselves after the end of the course. In taking this course, the Learner will also be shown the power of JupyterLab notebooks to facilitate literate programming. Through their participation in the class, learners will learn and understand FAIR (findability, accessibility, interoperability and reusability) best practices. We ask all participants to get a GitHub, Zenodo and ORCID accounts prior to the course. We ask for minimal background knowledge of the command line, simple commands in the shell environment, we enable a bit of self-learning from the repository to facilitate the acquisition of this knowledge. This work was powered on CAVATICA and INCLUDE Data Portal