NDLI: Concurrent class analysis identifies discriminatory variables from metabolomics data on isovaleric acidemia

Content Provider	Springer Nature Link
Author	Koekemoer, Gerhard Dercksen, Marli Allison, James Santana, Leonard Reinecke, Carolus J.
Copyright Year	2011
Abstract	Metabolomics data are typically complex and high dimensional. Multivariate dimension-reducing techniques have thus been developed for analysing metabolomics data to disclose underlying relationships, with principal component analysis (PCA) as the technique mostly applied. Despite its widespread use in metabolomics, PCA has shortcomings that limit its applicability. Several approaches have been made to overcome these limitations and we describe an advanced disjoint PCA (DPCA) model, termed concurrent class analysis and abbreviated as CONCA. CONCA is a new model, and is unique in linking DPCA models to a traditional PCA model. This is accomplished by restructuring the input data matrix, applying DPCA group models to the restructured data, and combining the DPCA models in order to replicate a traditional PCA. We applied the CONCA model to a metabolomics data set on isovaleric acidaemia (IVA), a rare inherited metabolic disorder. The outcome showed that three of the variables with high discrimination value identified through the CONCA analysis are prominent organic acid biomarkers for IVA. Moreover, three further minor metabolites associated with the disease, and two as a consequence of treatment, were likewise identified as important discriminatory variables. The benefit of the CONCA model thus is its ability to disclose information concerning each individual group and to identify the variables important in discrimination (VIDs) which are also responsible for group separation.
Starting Page	17
Ending Page	28
Page Count	12
File Format	PDF
ISSN	15733882
Journal	Metabolomics
Volume Number	8
Issue Number	1
e-ISSN	15733890
Language	English
Publisher	Springer US
Publisher Date	2011-07-07
Publisher Institution	Metabolomics Society
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Metabolomics Biomarker identification Variables important in discrimination Concurrent class analysis Isovaleric acidemia Developmental Biology Cell Biology Biochemistry Biomedicine general Molecular Medicine
Content Type	Text
Resource Type	Article
Subject	Endocrinology, Diabetes and Metabolism Clinical Biochemistry Biochemistry

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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