Analyzing metabolomics-based challenge tests
Vis, D.J. ; Westerhuis, J.A. ; Jacobs, D.M. ; Duynhoven, J.P.M. van; Wopereis, S. ; Ommen, B. van; Hendriks, M.M.W.B. ; Smilde, A.K. - \ 2015
Metabolomics 11 (2015)1. - ISSN 1573-3882 - p. 50 - 63.
glucose-tolerance test - insulin sensitivity - mathematical-models - component analysis - plasma metabolome - health - asca - reconstruction - phenotype - discovery
Challenge tests are used to assess the resilience of human beings to perturbations by analyzing responses to detect functional abnormalities. Well known examples are allergy tests and glucose tolerance tests. Increasingly, metabolomics analysis of blood or serum samples is used to analyze the biological response of the individual to these challenges. The information content of such metabolomics challenge test data involves both the disturbance and restoration of homeostasis on a metabolic level and is thus inherently different from the analysis of steady state data. It opens doors to study the variation of resilience between individuals beyond the classical biomarkers; preferably in terms of underlying biological processes. We review challenge tests in which metabolomics was used to analyze the biological response. Specifically, we describe strategies to perform statistical analyses on the responses and we will show some examples of these strategies applied to a postprandial challenge that was used to study a diet with anti-inflammatory properties. Finally we discuss open issues and give recommendation for further research.
Canonical correlation analysis of multiple sensory directed metabolomics data blocks reveals corresponding parts between data blocs
Doeswijk, T.G. ; Hageman, J.A. ; Westerhuis, J.A. ; Tikunov, Y.M. ; Bovy, A.G. ; Eeuwijk, F.A. van - \ 2011
Chemometrics and Intelligent Laboratory Systems 107 (2011)2. - ISSN 0169-7439 - p. 371 - 376.
variable selection - component analysis - multiblock - quality - fusion - models - pls
Multiple analytical platforms are frequently used in metabolomics studies. The resulting multiple data blocks contain, in general, similar parts of information which can be disclosed by chemometric methods. The metabolites of interest, however, are usually just a minor part of the complete data block and are related to a response of interest such as quality traits. Concatenation of data matrices is frequently used to simultaneously analyze multiple data blocks. Two main problems may occur with this approach: 1) the number of variables becomes very large in relation to the number of observations which may deteriorate model performance, and 2) scaling issues between the data blocks need to be resolved. Therefore, a method is proposed that circumvents direct concatenation of two data matrices but does uncover the shared and distinct parts of the data sets in relation to quality traits. The relevant part of the data blocks with respect to the quality trait of interest is revealed by partial least squares regression on each of the data blocks. The score vectors of both models that are predictive for the quality trait are then used in a canonicalcorrelationanalysis. Highly correlating score vectors indicate parts of the data blocks that are closely related. By inspecting the relevant loading vectors, the metabolites of interest are revealed
Risico-evaluatie OCAP-CO2 vanuit Abengoa: Deskstudie
Dueck, T.A. ; Dijk, C.J. van - \ 2011
Wageningen : PRI Agrosysteemkunde/WUR Glastuinbouw (Rapport / Plant Research International 404) - 12
fytotoxiciteit - risicoschatting - evaluatie - kooldioxide - componentenanalyse - glastuinbouw - nederland - phytotoxicity - risk assessment - evaluation - carbon dioxide - component analysis - greenhouse horticulture - netherlands
A priori and a posteriori methods in comparative evolutionary studies of host-parasite associations
Dowling, A.P.G. ; Veller, M.G.P. van; Hoberg, E.P. ; Brooks, D.R. - \ 2003
Cladistics-The International Journal of the Willi Hennig Society 19 (2003). - ISSN 0748-3007 - p. 240 - 253.
historical biogeography - vicariance biogeography - cladistic biogeography - parsimony analysis - area cladograms - phylogenetic systematics - component analysis - coevolution - speciation - statements
Brooks parsimony analysis (BPA) and reconciliation methods in studies of host-parasite associations differ fundamentally, despite using the same null hypothesis. Reconciliation methods may eliminate or modify input data to maximize fit of single parasite clades to a null hypothesis of cospeciation, by invoking different a priori assumptions, including a known host phylogeny. By examining the degree of phylogenetic congruence among multiple parasite clades, using hosts as analogs of taxa but not presuming a host phylogeny or any degree of cospeciation a priori, BPA modifies the null hypothesis of cospeciation if necessary to maintain the integrity of the input data. Two exemplars illustrate critical empirical differences between reconciliation methods and BPA: (1) reconciliation methods rather than BPA may select the incorrect general host cladogram for a set of data from different clades of parasites, (2) BPA rather than reconciliation methods provides the most parsimonious interpretation of all available data, and (3) secondary BPA, proposed in 1990, when applied to data sets in which host-switching produces hosts with reticulate histories, provides the most parsimonious and biologically realistic interpretations of general host cladograms. The extent to which these general host cladograms, based on cospeciation among different parasite clades inhabiting the same hosts, correspond to host phylogeny can be tested, a posteriori, by comparison with a host phylogeny generated from nonparasite data. These observations lead to the conclusion that BPA and reconciliation methods are designed to implement different research programs based on different epistemologies. BPA is an a posteriori method that is designed to assess the host context of parasite speciation events, whereas reconciliation methods are a priori methods that are designed to fit parasite phylogenies to a host phylogeny. Host-switching events are essential for explaining complex histories of host-parasite associations. BPA assumes coevolutionary complexity (historical contingency), relying on parsimony as an a posteriori explanatory tool to summarize complex results, whereas reconciliation methods, which embody formalized assumptions of maximum cospeciation, are based on a priori conceptual parsimony. Modifications of basic reconciliation methods, embodied in TreeMap 1.0 and TreeMap 2.02, represent the addition of weighting schemes in which the researcher specifies allowed departures from cospeciation a priori, with the result that TreeMap results more closely agree with BPA results than do reconciled tree analysis results. (C) 2003 The Willi Hennig Society. Published by Elsevier Science (USA). All rights reserved.
Cladistic and phylogenetic biogeography: the art and the science of discovery
Veller, M.G.P. van; Brooks, D.R. ; Zandee, R. - \ 2003
Journal of Biogeography 30 (2003). - ISSN 0305-0270 - p. 319 - 329.
historical biogeography - vicariance biogeography - parsimony analysis - area cladograms - component analysis - a-posteriori - speciation - statements - dispersal - assumption-1
All methods used in historical biogeographical analysis aim to obtain resolved area cladograms that represent historical relationships among areas in which monophyletic groups of taxa are distributed. When neither widespread nor sympatric taxa are present in the distribution of a monophyletic group, all methods obtain the same resolved area cladogram that conforms to a simple vicariance scenario. In most cases, however, the distribution of monophyletic groups of taxa is not that simple. A priori and a posteriori methods of historical biogeography differ in the way in which they deal with widespread and sympatric taxa. A posteriori methods are empirically superior to a priori methods, as they provide a more parsimonious accounting of the input data, do not eliminate or modify input data, and do not suffer from internal inconsistencies in implementation. When factual errors are corrected, the exemplar presented by M.C. Ebach & C.J. Humphries (Journal of Biogeography, 2002, 29, 427) purporting to show inconsistencies in implementation by a posteriori methods actually corroborates the opposite. The rationale for preferring a priori methods thus corresponds to ontological rather than to epistemological considerations. We herein identify two different research programmes, cladistic biogeography (associated with a priori methods) and phylogenetic biogeography (associated with a posteriori methods). The aim of cladistic biogeography is to fit all elements of all taxon–area cladograms to a single set of area relationships, maintaining historical singularity of areas. The aim of phylogenetic biogeography is to document, most parsimoniously, the geographical context of speciation events. The recent contribution by M.C. Ebach & C.J. Humphries (Journal of Biogeography, 2002, 29, 427) makes it clear that cladistic biogeography using a priori methods is an inductivist/verificationist research programme, whereas phylogenetic biogeography is hypothetico-deductivist/falsificationist. Cladistic biogeography can become hypothetic-deductive by using a posteriori methods of analysis