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OPLS-DA Analysis


To provide OPLS-DA analysis services to global customers, CD Mitochondria relies on a professional team, rich experience, and mature platforms. The relationship model between metabolite expression and sample categories is established by partial least square regression to predict sample categories.

Orthogonal PLS-DA (OPLS-DA) is a supervised discriminant analysis statistical method, which is different from the PAC method. CD Mitochondria uses this method to establish a model of the relationship between metabolite expression and sample categories by partial least square regression to predict sample categories.

In OPLS-DA, a regression model is constructed between multivariate data and response variables that contain only class information. The obvious advantage of OPLS-DA over PLS-DA (Partial Least-Squares Discriminant Analysis) is that a single component can be used as a predictive variable for a category, while other components describe changes that are orthogonal to the first predictive component.

CD Mitochondria establishes a pairwise OPLS-DA model, and the parameter evaluation of the model is provided in tabular form. At the same time, the influence and explanatory ability of the expression patterns of each metabolite on the classification of each sample are measured by calculating the variable importance for the projection (VIP), to assist the screening of marker metabolites (usually the VIP value > 1.0 is used as the screening criterion).

CD Mitochondria always provides you with customized services for mitochondrial research, and our one-stop research and analysis platform can meet all your research needs.

Our Advantages

  • Rich experience in the OPLS-DA Analysis
  • Outstanding research team
  • Unique integrated service for mitochondrial research
  • Reliable data and results
  • Rapid turnaround and cost-effective

CD Mitochondria has the most professional team to serve customers around the world. If you have any questions about the content of this service, please feel free to contact us. We look forward to your contact.

References

  1. Blasco H., et al. “Comparative analysis of targeted metabolomics: Dominance-based rough set approach versus orthogonal partial least square-discriminant analysis. ” Journal of Biomedical Informatics, 2015, 53: 291-299.
  2. Worley B., Powers R. “ PCA as a practical indicator of OPLS-DA model reliability. ”Curr Metabolomics, 2016, 4(2): 97-103.
For Research Use Only. Not For Clinical Use Or Individual Users.

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