Nowadays, multiple testing issues appear routinely in omics data. A huge amount of literature has appeared, proposing different methods to bound the number of false positives in the analyses, and the most powerful tool that allows such a control is desired. In this work we show through two examples from metabolomics data that "the" best method, to be applied blindly, does not exist. A careful evaluation on which method to use has to be done in every situation
Giordan, M.; Franceschi, P.; Wehrens, H.R.M.J. (2013). Multiple testing in metabolomics. In: High-Throughput Omics & Data Integration Workshop (COST action SeqAhead), Barcelona, Febrauary 12-15, 2013. handle: http://hdl.handle.net/10449/23462
Multiple testing in metabolomics
Giordan, Marco;Franceschi, Pietro;Wehrens, Herman Ronald Maria Johan
2013-01-01
Abstract
Nowadays, multiple testing issues appear routinely in omics data. A huge amount of literature has appeared, proposing different methods to bound the number of false positives in the analyses, and the most powerful tool that allows such a control is desired. In this work we show through two examples from metabolomics data that "the" best method, to be applied blindly, does not exist. A careful evaluation on which method to use has to be done in every situation
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