Multivariate projection methods such as PCA and PLS provide data visualisation and predictive, validatable models. Principal Components Analysis (PCA) is invaluable as a visualisation and quality assurance tool and the recently introduced Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) method enables rapid identification of biomarker candidates.
For more detailed information, see the application notes "Metabonomics", "Analysing Omics Data", and "Mass Spec Based Metabonomics".
System Biology is an area increasing in industry. One of its challenges is the large amount of data collected. These data can be transferred into information by applying Multivariate Data Analysis (MVA) in general, and Orthogonal Partial Least Squares Discriminate analysis (OPLS-DA) in principal.
If the coming year seems to be stressful year here is some encouraging news
The latest research from Metabomics GmbH and Nestle “provides strong evidence that a daily consumption of 40 g of dark chocolate during a period of 2 weeks is sufficient to modify the metabolism of free living and healthy human subjects, as per variation of both host and gut microbial metabolism.” It is concluded that persons with a higher anxiety trait got “partly normalized stress related energy metabolism”
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Umetrics has the strength in offering OPLS and training in analysis of OMICS data. For further information you are free to download a DEMO of SIMCA-P+ where OPLS is available. Umetrics is also offering dedicated training courses in applying MVA to OMICS data, see further Umetrics Academy for location and date for the Multivariate Data Analysis for Omics training.
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Umetrics Academy
