diff --git a/index.md b/index.md index f9c4fe9..7c52a1b 100644 --- a/index.md +++ b/index.md @@ -4,7 +4,9 @@ [Cloud-SPAN](https://cloud-span.york.ac.uk) is a project run by the Department of Biology at the University of York with the aim to training researchers in the experimental design and analysis of 'omics data using cloud-based High Performance Computing (HPC) resources. -This course teaches how to create and manage your own Cloud-SPAN Amazon Web Services (AWS) **instance**, which is a Linux virtual machine configured with 'omics data and software analysis tools. The instance you will create is the same instance that is used in the Cloud-SPAN courses [Prenomics](https://cloud-span.github.io/prenomics00-intro/) and [Genomics](https://cloud-span.github.io/00genomics). As such it is an excellent vehicle for those who want to self-study those courses or have taken them and now want to practice further or with other materials in their own time. +This course teaches how to create and manage your own Cloud-SPAN Amazon Web Services (AWS) **instance**, which is a Linux virtual machine configured with 'omics data and software analysis tools. The instance you will create is the same instance that is used in the Cloud-SPAN courses [Prenomics](https://cloud-span.github.io/prenomics00-intro/) and [Genomics](https://cloud-span.github.io/00genomics). + +If you attend tutor-led editions of Cloud-SPAN's [Prenomics](https://cloud-span.github.io/prenomics00-intro/) and [Genomics](https://cloud-span.github.io/00genomics) courses you do not need to create your own instance. We will do that for you! But if would like to practice afterwards, or study the courses in your own time, you will need to create an instance first. You will learn (1) how to open and configure your AWS account, which will enable you to use any AWS service; (2) how to create and manage (start, stop and terminate) your instance; and (3) the cost of using your instance. @@ -18,7 +20,7 @@ The course is designed for 2-3 hours of self-study. > > Tablets and mobile phones are not suitable for taking the course, as the screenshots that are shown through the course were taken from desktop screens. > -> Please note that this course does **not** cover **using your instance**: tasks such as managing the data in your instance or running genomics analyses are covered in the [Prenomics](https://cloud-span.github.io/prenomics00-intro/) and [Genomics](https://cloud-span.github.io/genomics01-intro) courses. The relevant sections of these courses are below under the heading **Where to go from here.** +> Please note that this course does **not** cover **using your instance**: tasks such as managing the data in your instance or running genomics analyses are covered in the [Prenomics](https://cloud-span.github.io/prenomics00-intro/) and [Genomics](https://cloud-span.github.io/genomics01-intro). {: .prereq} ## Background @@ -38,14 +40,14 @@ The largest cloud providers at the time of writing in terms of market share are | Lesson | Overview | | -------------------------- | ---------| | [Open your AWS account](https://cloud-span.github.io/create-aws-instance-1-open-account/) | Learn how to open and configure your AWS account, which enables you to use AWS services.| -| [Create and manage your AWS instance](https://cloud-span.github.io/create-aws-instance-2-manage-instance/)| Learn how to create, start, stop, and terminate your instance using the AWS Console, and how to login to your instance. See section below `Where to go from here` for related resources. | +| [Create and manage your AWS instance](https://cloud-span.github.io/create-aws-instance-2-manage-instance/)| Learn how to create, start, stop, and terminate your instance using the AWS Console, and how to login to your instance. | | [AWS Costs Explained](https://cloud-span.github.io/create-aws-instance-3-costs-explained/) | Learn about the costs of using your Cloud-SPAN AWS instance, the AWS Free Tier and Research Credits available.| ## Where to go from here +Once you have created your instance you will will be able to follow Cloud-SPAN's [Prenomics](https://cloud-span.github.io/prenomics00-intro/) and [Genomics](https://cloud-span.github.io/00genomics) modules. -| Resource | Description | +| Module | Description | | -------------------------- | ---------| -| [Installing Git Bash](https://cloud-span.github.io/prenomics00-intro/setup.html)| Only Windows users need these instructions to install the Git Bash program which is needed to login to their instance. (Linux and MacOs users should use the `terminal` program to login to their instance.)| -| [Logging to your instance](https://cloud-span.github.io/prenomics01-file-directories/02-logging-onto-cloud/) | Instructions to login to your instance (a lesson from the Cloud-SPAN Prenomics course).| -| [Using the Shell](https://cloud-span.github.io/prenomics02-command-line/) | Instructions for you to use your instance through the command line interface, also known as the Shell (a lesson from the Cloud-SPAN Prenomics course).| -| [Running 'omics applications](https://cloud-span.github.io/00genomics/)| Examples of using 'omics data and applications (the foundation Cloud-SPAN Genomics course). | +| [Prenomics](https://cloud-span.github.io/prenomics00-intro/)| Prenomics is a 4 - 6 hour module that teaches the basics of command-line programming, including: (1) file directory structure, (2) use of command-line utilities to connect to and use cloud computing and storage resources and (3) basic shell commands for file navigation and basic script writing. It is designed to prepare people for [Genomics](https://cloud-span.github.io/00genomics) but, depending on previous experience, you may not need it. There is short (~5 minutes) [Self-assessment Quiz](https://shiny.york.ac.uk/er13/prenomics-quiz/#section-why) to help you decide if you would benefit from attending Prenomics before the Genomics.| +| [Genomics](https://cloud-span.github.io/00genomics/) | Genomics is a 8 - 12 hour module that teaches data management and analysis for genomics research including: (1) best practices for organization of bioinformatics projects and data, (2) use of command-line utilities to connect to and use cloud computing and storage resources, (3) use of command-line tools for data preparation, (4) use of command-line tools to analyze sequence quality and perform and automate variant calling. | +