Dear all,
we still have a few places left on our course "Metabolomics: from study design to data analysis"
Dates: 25-29 November 2019
Where: Free University of Berlin (Germnay)
Instructor: Dr. Pietro Franceschi (https://scholar.google.it/citations?...kzgAAAAJ&hl=en)
OVERVIEW
The aim of the course is to cover some of the fundamental aspects of metabolomics from the “data analyst” point of view. The aim is to cover all the key aspects which have to be considered to set-up a successful metabolomics investigation, from the practical issues related to study/analytical design to data pre-processing and statistical analysis. The course will be delivered relying on a mixture of lectures, computer-based practical sections, and group discussions.
Prerequisites
Familiarity with R will be assumed. A full day of the course will be however devoted to a fast introduction to data carpentry and visualization in R. A basic experience in metabolomics will be welcomed.
Outcomes
The objective of the course is to make the participants familiar with metabolomics and, in particular, to data analysis of metabolomics data (targeted and untargeted). The course will also constitute an excellent primer to the application of univariate and multivariate statistics to complex datasets of chemical origin.
Programme
Monday: 9:30 - 17:30
Metabolomics: what, why, how
What is metabolomics (targeted and untargeted)
Study design considerations
Analytical chemistry in metabolomics
Integrating Data Analysis and Data Collection
Data sharing and reproducibility
Group activity: design your study
Tuesday: 9:30 - 17:30
From zero to R
R and RStudio
Visualizing your data
Data carpentry (practical)
Multivariate visualization by PCA
Group discussion
Wednesday 9:30 - 17:30
Preprocessing of MS based untargeted metabolomics data
The pre-processing workflow
Let’s do it in R with xcms
Are my data OK?
Quality assessment
Outliers
Missing values and imputation
From Features to compounds … annotation
Group discussion: targeted vs untargeted metabolomics
Thursday 9:30 - 17:30
Let’s talk about Statistics
Univariate statistics
Introduction to statistical testing and modeling
Multiple testing
Multivariate statistics
Classification and regression
Model tuning and validation
PLS and RandomForest
Group Discussion
Friday 9:30 - 17:30
Putting Everything Together
Group Activity: running and presenting a full data analysis task from A to Z
Q&A: Open space for recap, clarifications, and open discussion
Full list of our courses and Workshops: https://www.physalia-courses.org/courses-workshops
Should you have any questions, please do not hesitate to contact us: [email protected]
All the best, Carlo
Carlo Pecoraro, Ph.D
Physalia-courses DIRECTOR
[email protected]
Twitter: @physacourses
mobile: +49 17645230846
we still have a few places left on our course "Metabolomics: from study design to data analysis"
Dates: 25-29 November 2019
Where: Free University of Berlin (Germnay)
Instructor: Dr. Pietro Franceschi (https://scholar.google.it/citations?...kzgAAAAJ&hl=en)
OVERVIEW
The aim of the course is to cover some of the fundamental aspects of metabolomics from the “data analyst” point of view. The aim is to cover all the key aspects which have to be considered to set-up a successful metabolomics investigation, from the practical issues related to study/analytical design to data pre-processing and statistical analysis. The course will be delivered relying on a mixture of lectures, computer-based practical sections, and group discussions.
Prerequisites
Familiarity with R will be assumed. A full day of the course will be however devoted to a fast introduction to data carpentry and visualization in R. A basic experience in metabolomics will be welcomed.
Outcomes
The objective of the course is to make the participants familiar with metabolomics and, in particular, to data analysis of metabolomics data (targeted and untargeted). The course will also constitute an excellent primer to the application of univariate and multivariate statistics to complex datasets of chemical origin.
Programme
Monday: 9:30 - 17:30
Metabolomics: what, why, how
What is metabolomics (targeted and untargeted)
Study design considerations
Analytical chemistry in metabolomics
Integrating Data Analysis and Data Collection
Data sharing and reproducibility
Group activity: design your study
Tuesday: 9:30 - 17:30
From zero to R
R and RStudio
Visualizing your data
Data carpentry (practical)
Multivariate visualization by PCA
Group discussion
Wednesday 9:30 - 17:30
Preprocessing of MS based untargeted metabolomics data
The pre-processing workflow
Let’s do it in R with xcms
Are my data OK?
Quality assessment
Outliers
Missing values and imputation
From Features to compounds … annotation
Group discussion: targeted vs untargeted metabolomics
Thursday 9:30 - 17:30
Let’s talk about Statistics
Univariate statistics
Introduction to statistical testing and modeling
Multiple testing
Multivariate statistics
Classification and regression
Model tuning and validation
PLS and RandomForest
Group Discussion
Friday 9:30 - 17:30
Putting Everything Together
Group Activity: running and presenting a full data analysis task from A to Z
Q&A: Open space for recap, clarifications, and open discussion
Full list of our courses and Workshops: https://www.physalia-courses.org/courses-workshops
Should you have any questions, please do not hesitate to contact us: [email protected]
All the best, Carlo
Carlo Pecoraro, Ph.D
Physalia-courses DIRECTOR
[email protected]
Twitter: @physacourses
mobile: +49 17645230846