Participants will become familiar with standardised workflows as well as with the current state of experimental design, data acquisition (LC-MS, MS imaging), processing, and modelling.
In addition, they will learn about community standards and sharing in metabolomics, particularly through the use of EMBL-EBI鈥檚 MetaboLights repository and Galaxy infrastructure. Participants will learn through hands-on tutorials to use tools available for data analysis and data submission. Additionally, case studies will be discussed to show how to employ the week鈥檚 learning.
Who is this course for?
This course is aimed at researchers who are new to the field of metabolomics and wish to learn about the process of conducting a metabolomics study. The course will benefit those who are planning to integrate metabolomics into their work, either moving into the field or as an investigator from other -omics. We will primarily focus on a basic introduction to metabolomics with worked examples using a predesigned LC-MS analysis workflow.
Basic knowledge of programming languages can be an advantage (e.g. you understand the basic command line functioning, you can navigate Galaxy tutorials). We recommend these free resources or other similar ones:
The Unix Shell: https://swcarpentry.github.io/shell-novice/
A Short Introduction to Galaxy: https://www.youtube.com/watch?v=IRdlOcVgjRY
What will I learn?
Learning outcomes
After the course you should be able to:
Perform basic data acquisition, processing, and modelling in metabolomics
Estimate what factors contribute to designing a successful metabolomics study
Describe the issues of data standards and sharing in metabolomics
Access and use public metabolomics resources
Cite the principles of creating a standardised workflow to perform basic metabolomics analysis
Course content
During this course you will learn about:
Basic metabolomics experimental design, acquisition, and analysis
Public metabolomics resources: MetaboLights, Galaxy
Open source metabolomics tools made available through customisable workflows
Case study based on a published/public example
In addition, they will learn about community standards and sharing in metabolomics, particularly through the use of EMBL-EBI鈥檚 MetaboLights repository and Galaxy infrastructure. Participants will learn through hands-on tutorials to use tools available for data analysis and data submission. Additionally, case studies will be discussed to show how to employ the week鈥檚 learning.
Who is this course for?
This course is aimed at researchers who are new to the field of metabolomics and wish to learn about the process of conducting a metabolomics study. The course will benefit those who are planning to integrate metabolomics into their work, either moving into the field or as an investigator from other -omics. We will primarily focus on a basic introduction to metabolomics with worked examples using a predesigned LC-MS analysis workflow.
Basic knowledge of programming languages can be an advantage (e.g. you understand the basic command line functioning, you can navigate Galaxy tutorials). We recommend these free resources or other similar ones:
The Unix Shell: https://swcarpentry.github.io/shell-novice/
A Short Introduction to Galaxy: https://www.youtube.com/watch?v=IRdlOcVgjRY
What will I learn?
Learning outcomes
After the course you should be able to:
Perform basic data acquisition, processing, and modelling in metabolomics
Estimate what factors contribute to designing a successful metabolomics study
Describe the issues of data standards and sharing in metabolomics
Access and use public metabolomics resources
Cite the principles of creating a standardised workflow to perform basic metabolomics analysis
Course content
During this course you will learn about:
Basic metabolomics experimental design, acquisition, and analysis
Public metabolomics resources: MetaboLights, Galaxy
Open source metabolomics tools made available through customisable workflows
Case study based on a published/public example
