Document Detail

Normalising and integrating metabolomics data.
MedLine Citation:
PMID:  23150939     Owner:  NLM     Status:  Publisher    
Metabolomics research often requires the use of multiple analytical platforms, batches of samples, and laboratories, any of which can introduce a component of unwanted variation. In addition, every experiment is subject to within platform and other experimental variation, which often includes unwanted biological variation. Such variation must be removed in order to focus on the biological information of interest. We present a broadly applicable method for the removal of unwanted variation arising from various sources for the identification of differentially abundant metabolites, and hence, for the systematic integration of data on the same quantities from different sources. We illustrate the versatility and the performance of the approach in four applications, and show that it has several advantages over the existing normalisation methods.
Alysha M De Livera; Daniel Anthony Dias; David De Souza; Thusita Rupasinghe; James Pyke; Dedeja L Tull; Ute Roessner; Malcolm J McConville; Terence P Speed
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-11-14
Journal Detail:
Title:  Analytical chemistry     Volume:  -     ISSN:  1520-6882     ISO Abbreviation:  Anal. Chem.     Publication Date:  2012 Nov 
Date Detail:
Created Date:  2012-11-15     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0370536     Medline TA:  Anal Chem     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
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