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Multivariate Data Analysis for Omics

Multivariate Analysis for "Omics"
Multivariate data analysis is essential in the process of extracting information from the complex data sets involved in “omics” studies. Discover how to build valid and predictive models based on data from genomic, proteomic and metabolomic studies, with the latest multivariate techniques. The focus on this course is how to use state-of art multivariate tools to extract putative biomarkers in a statistically significant way. 
The course is composed of lectures, demonstrations and computer exercises using SIMCA-P+12 software on real-life datasets. Examples from plant biology and medicine will be used to highlight the usefulness of the applied strategies.

After completing the course, participants will know how to:
• Insights on chemometrics strategies for ”omics” studies
• Apply PCA to detect outliers, trends and patterns in "omics" data
• An awareness of sources of variability and the effect on modeling and interpretation
• Understanding of how to use OPLS in classification 
•  Understanding on how to compare multiple treatments
• Understanding on how to apply multivariate tools for putative biomarker identification
• Validate models for robustness and predictability

Who should participate?
The course is intended for researchers involved in “omics” studies with little or no knowledge in multivariate data analysis. The examples presented in the lectures are focused on MS- and NMR-based metabolomics, for consistency. The exercises include genomics, proteomics and metabolomics data sets so participants from different field can choose from their own interest. Practice on own data is also welcome and appreciated.

Course schedule
Lunch daily between 12:00 - 13:00
Day one
09:00 Introduction to multivariate data analysis 
Principal component analysis, PCA
Apply PCA to detect outliers, trends and patterns in metabolomic data
Interpret models to gain scientific insights
Exercises in SIMCA-P+
17:00 End of lectures and exercises and course dinner
Day two
09:00 From PCA to Orthogonal projections to latent structures, OPLS
Putative biomarkers identification using OPLS
How to compare multiple treatments
Validate models for robustness and predictability
Exercises in SIMCA-P+ and discussions
Course summary
17:00 End of course

Cost and conditions
Course fee (+VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. OBSERVE THAT OWN LAPTOPS IS REQUIERED FOR EXCERCISES. PROGRAM INSTALLATION INSTRUCTIONS WILL BE SENT OUT WITH THE FINAL COURSE INFORMATION. Course application is binding. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s).
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.

COURSE INFORMATION

Course length: 2 days
Location: Sweden, Malmoe/Copenhagen
Start date: 2010-11-16
Price: 995 EUR
Contact: umetrics.academy@umetrics.com

Please visit www.umetrics.com/training for more information and registration.

No prior knowledge of statistics is required, knowledge about in-house data base structure is beneficial.