Learning path topics
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Licensing data
This section offers the basic knowledge and tools to effectively manage licensing within bioinformatics research. Specifically, the included presentation provides guidance on understanding different types of licenses for both software and data, detailing their legal and practical implications....
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Metadata
This section introduces the role and importance of metadata in research data management and its impact on making data FAIR. Learners explore metadata standards, controlled vocabularies, and ontologies, and learn how to apply them to describe their data effectively.
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Module 1: FAIR Data Management
This FAIR data management learning pathway empowers clinicians to effectively organise, document, and share patient data for research and improved care.”
Time estimation: 1 hour 20 minutes
Learning objectives:
- Learn the FAIR principles
- Recognise the relationship between FAIR and...
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Module 1: Introduction to Galaxy [and Sequence analysis]
Get a first look at the Galaxy platform for data analysis. We start with a short introduction (video slides & practical) to familiarize you with the Galaxy interface, and then proceed with a slightly longer introduction tutorials where you perform a first, very simple, analysis.
Time...
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Module 1: Introduction to Galaxy [and Single Cell RNA Sequence analysis]
Get a first look at the Galaxy platform for data analysis. We start with a short introduction (video slides & practical) to familiarize you with the Galaxy interface, and then proceed with a short tutorial of how to tag - and organise! - your history.
Time estimation: 1 hour
Learning...
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Module 1: Learning principles
This module covers the following questions:
- What are the main principles that drive learning?
- How can these principles be applied to training and teaching?
At the end of this module, learners should be able to:
- Describe how learning works according to a few learning models ...
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Module 1: Preparing the dataset
This tutorial takes you from the large files containing raw scRNA sequencing reads to a smaller, combined cell matrix.
Time estimation: 3 hours
Learning objectives:
- Generate a cellxgene matrix for droplet-based single cell sequencing data
- Interpret quality control (QC) plots to...
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Module 1: R in Galaxy
Get a first understanding of how to code using R fully using the Galaxy infrastructure. The first part will introduce the basic concepts of R, whereas the second part will focus on providing some advanced concepts around data manipulation.
Time estimation: 5 hours
Learning objectives:
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Module 2: Basics of Genome Sequence Analysis
When analysing sequencing data, you should always start with a quality control step to clean your data and make sure your data is good enough to answer your research question. After this step, you will often proceed with a mapping (alignment) or genome assembly step, depending on whether you have...
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Module 2: Design and plan session, course, materials
This module covers the following questions:
- What is the structured approach to course design?
- How to articulate learning outcomes commensurate with the cognitive complexity of the target learning?
- How to devise learning experiences and course content?
- What are the steps that can...