Multivariate Analysis of Multiple Datasets: a Practical Guide for Chemical Ecology

Journal of Chemical Ecology
Maxime R HervéKim-Anh Lê Cao

Abstract

Chemical ecology has strong links with metabolomics, the large-scale study of all metabolites detectable in a biological sample. Consequently, chemical ecologists are often challenged by the statistical analyses of such large datasets. This holds especially true when the purpose is to integrate multiple datasets to obtain a holistic view and a better understanding of a biological system under study. The present article provides a comprehensive resource to analyze such complex datasets using multivariate methods. It starts from the necessary pre-treatment of data including data transformations and distance calculations, to the application of both gold standard and novel multivariate methods for the integration of different omics data. We illustrate the process of analysis along with detailed results interpretations for six issues representative of the different types of biological questions encountered by chemical ecologists. We provide the necessary knowledge and tools with reproducible R codes and chemical-ecological datasets to practice and teach multivariate methods.

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Citations

Jan 31, 2019·Annals of Botany·Colin M OriansCaroline Müller
Oct 8, 2019·Journal of Economic Entomology·Flore MasDavid Maxwell Suckling
Jul 30, 2020·Journal of Evolutionary Biology·Nathan J ButterworthPhillip G Byrne
Dec 6, 2019·Scientific Reports·Patricia Nagnan-Le MeillourMatthieu Keller
Aug 1, 2020·Journal of Analytical Methods in Chemistry·Muhammad Aslam, Osama H Arif
Jun 18, 2020·Frontiers in Plant Science·Eric R ScottColin M Orians
Apr 26, 2020·Journal of Chemical Ecology·Flore MasDavid Maxwell Suckling
Jun 29, 2021·The Science of the Total Environment·Christine BeckerAnne-Violette Lavoir

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Methods Mentioned

BETA
PCA
PCAs

Software Mentioned

CIA
DA
DIABLO
OnPLS
- Inertia Analysis (
Procrustean
PPLS
PROTEST
R
O2PLS

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