Learning resources
These materials provide an introduction to R for complete beginners. It teaches you how to find your way round RStudio, use the basic data types and structures in R and how to organise your work with scripts and projects. It also teaches you how to import data, summarise it and create and format a graph. The materials are aimed at beginners and assumes no prior experience of coding.
After completing the materials you will be able to;
find your way around RStudio
use the basic data types and structures in R
organise your work with scripts and projects
import data, summarise it and create and format a graph
If you would to complete the Prenomics and Genomics materials using the self-study learning mode you will need to start by creating your own Amazon Web Services (AWS) instance on your own AWS account.
Registration
This course is free of charge, however we ask that you register for the Self-Study learning mode using the registration button below, so we have your details and we can provide you with additional information.
Study Mode
This course is a self-study course and you can work through the online materials at your own pace. If you require any additional support whilst completing this course, there will be an informal 1 hour weekly drop in session via zoom to ask instructors any questions, you will be provided with information on this when you register.
Pre-requisites
Knowledge: this course assumes no prior experience with the tools covered in the workshop. However, learners are expected to have some familiarity with biological concepts, including the concept of genomic variation within a population.
Overview & programme
How to create and manage an AWS instance derived from the Cloud-SPAN AWS Machine Image (AMI).
Topics
Creating an AWS account, Estimated resources needed for our instance, Getting research credits, Cost without research credits, How to reuse our instances on AWS, Creating one new instance and Ending an instance
Target audience
PhD Students & Researchers
Learning outcomes
Following completion of this course, learners will be able to: create and manage an AWS instance derived from the Cloud-SPAN AWS Machine Image (AMI).
Understanding your file system and using the command line
This workshop on understanding your file system and using the command line is available as a self-study module.
Registration
This course is free of charge, however we ask that you register for the Self-Study learning mode using the registration button below, so we have your details and we can provide you with additional information.
Study Mode
This course is a self-study course and you can work through the online materials at your own pace. If you require any additional support whilst completing this course, there will be an informal 1 hour weekly drop in session via zoom to ask instructors any questions, you will be provided with information on this when you register.
Pre-requisites
Knowledge: this course assumes no prior experience with the tools covered in the workshop. However, learners are expected to have some familiarity with biological concepts, including the concept of genomic variation within a population. To ensure that you would benefit from participating in this course please complete the short self-assessment quiz. Please note, if you are completing the course on a self-study learning path you will need to complete the Creating your own instance course beforehand.
Software: view the required software set-up.
Topics: Understanding your file system
Intro to local and remote files, hierarchical structure of files and folders, how to create a Cloud-SPAN folder
Intro to the files which will be used in the Genomics course and
Logging onto the Cloud
Introducing the Shell
Using the command line
Navigating Files and Directories
Working with Files and Directories
Redirection
Target audience
PhD Students & Researchers
Learners who are intending to do bioinformatics but do not have any prior experience.
Learners who wish to complete the Genomics Course
Learning outcomes
Following completion of this course, learners will be able to;
explain the hierarchical structure of a file system
understand the structure of the file system on their own machine
find, create, move and delete folders and files on their machine
explain what is meant by a working directory, a path and a relative path
write down paths that they will need for the Prenomics and Genomics courses
describe the files and file structure used in Prenomics and Genomics courses
start a Terminal (Mac) or Git Bash Terminal (Windows)
navigate a file system using the command line
log in to and exit their AWS instance (the cloud)
use common commands such as ls, pwd and cd, on the command line
This course teaches data management and analytical skills for genomic research.
Registration
This course is free of charge, however we ask that you register for the Self-Study learning mode using the registration button below, so we have your details and we can provide you with additional information.
Pre-requisites
Knowledge: learners should have completed the Prenomics course or be able to successfully complete the self-assessment quiz. Learners are also expected to have some familiarity with biological concepts, including the concept of genomic variation within a population. Please note, you will need to complete the Creating your own instance course beforehand.
Software: view the required software set-up.
Programme
Topics: Session 1 - Project management for cloud genomics
Learn how to structure your data and metadata
Plan for an NGS project
Learn about the benefits of cloud computing
Session 2 - Data preparation and organisation
Learn how to structure your data and metadata
Plan for an NGS project
Learn about the benefits of cloud computing
Session 3 - Assessing read quality; trimming and filtering reads
Trimming and filtering, learn how to filter out poor quality data
Assessing read quality
Session 4 - Finding sequence variants
Understand the steps involved in variant calling
Describe the types of data formats encountered during variant calling
Use command line tools to perform variant calling
Instructors will give a demonstration on how to use the Integrative Genomics Viewer (IGV), an interactive tool for the visual exploration of genomic data.
Target audience
Learners who have completed the Prenomics Course
PhD Students & Researchers
This course would be appropriate for learners with experience using the command line, who are expecting to generate a dataset in the future or those who already have a dataset and would like guidance on how to analyse it.
Learning outcomes
Following completion of this course, learners will be able to
structure their data and metadata and plan for an NGS project
organise and document genomics data and bioinformatics workflows
understand what information is needed by a sequencing facility
gain practice navigating file systems, creating, copying, moving, and removing files and directories
use command-line tools to assess read quality and perform quality control
align reads to a reference genome, and identify and visualise sequence variants
work with Amazon AWS cloud computing and transfer data between a local computer and cloud resources