MVDA Omics Open Course 2 days, 1p

Who should attend:

Researchers and scientists who want to model Omics data (Metabo(n/l)omics, Proteomics, Genomics, etc. with data from LC-MS, GC-MS or NMR spectrum, Gel Electrophoresis, Fluorescence measurements, Gene Chip Arrays, etc.) from all sectors of biological/pharmaceutical/medical/chemical/F&B/ with a lot of process understanding but with no or limited statistical background..

Info:

Using the latest multivariate techniques, participants will learn how to build multivariate prediction models, from reading the data until defining the model for a real-life application. The course is composed of lectures, demonstrations, and computer exercises in software SIMCA® /SIMCA® Omics Skin based on real-life datasets.

To guide the attendees through their journey from importing the omics dataset to a multivariate biomarker identification based on their omics data.

Topics include:

• Organization, visualization, and treatment of different types of data.
• Principal components analysis (PCA) for overview of tables, finding outliers, groups, and trends in data.
• Orthogonal Projections to Latent Structures - Discriminant Analysis (OPLS-DA) for class discrimination and biomarker identification.
• Multiblock Orthogonal Component Analysis (MOCA) for data integration and fusion in system biology.

SCHEDULE

Session 1 (3.5h): Introduction to MVDA

• Introduction to Sartorius Digital Solutions.
• Introduction to omics data.
• Data analysis objectives.
• Workflow in omics.
• Introduction to Principal Component Analysis (PCA) for overview of data tables.
• Software click-along demo.

Session 2 (3.5h): OPLS discriminant analysis (OPLS-DA), Two-group problem, Visualization.

• Introduction to discriminant analysis, focus on two-group problem.
• Introduction to Omics skin and its Analysis wizard.
• How the Analysis wizard works, the S-plot.
• Plots after leaving Analysis wizard.
• Additional useful plots for visualization.
• Software click-along demo.

Session 3 (3.5h): More OPLS-DA Theory, Three-group problem.

• How to handle the three-group problem.
• How to handle multi-group investigations.
• Identifying shared and unique variation,the SUS-plot.
• More on OPLS-DA TheorySoftware click-along demo.

Session 4 (3.5h): Advanced Omics Applications

• Analysis of Omics Data With Few Samples.
• Ensuring quality data.
• Analyzing Group vs Group Data.
• Analyzing Difference data.
• Group to Group vs Difference Data.
• A Multivariate Approach to Systems Biology.
• Software click-along demo.
• Course debriefing and final Q&A.