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Plant Cell. 2015 Aug;27(8):2088-94. doi: 10.1105/tpc.15.00238. Epub 2015 Jul 28.

Reassess the t Test: Interact with All Your Data via ANOVA.

Author information

1
Department of Plant Biology, University of California, Davis, California 95616.
2
DynaMo Center of Excellence, University of Copenhagen, DK-1871 Frederiksberg C, Denmark.
3
Gregor Mendel Institute, Austrian Academy of Sciences, Vienna Biocenter, 1030 Vienna, Austria.
4
Department of Clinical Sciences, Division of Computational Genetics, Swedish University of Agricultural Sciences, SE-75007 Uppsala, Sweden.
5
School of Life Sciences and Warwick Systems Biology Centre, University of Warwick, Coventry CV4 7AL, United Kingdom.
6
Department of Plant Biology, University of Minnesota, St. Paul, Minnesota 55108.
7
Department of Biology, Washington University in St. Louis, St. Louis, Missouri 63130.
8
Microbial and Plant Genomics Institute and Department of Plant Biology, University of Minnesota, St. Paul, Minnesota 55108.
9
DynaMo Center of Excellence, University of Copenhagen, DK-1871 Frederiksberg C, Denmark Department of Plant Sciences, University of California, Davis, California 95616 kliebenstein@ucdavis.edu.

Abstract

Plant biology is rapidly entering an era where we have the ability to conduct intricate studies that investigate how a plant interacts with the entirety of its environment. This requires complex, large studies to measure how plant genotypes simultaneously interact with a diverse array of environmental stimuli. Successful interpretation of the results from these studies requires us to transition away from the traditional standard of conducting an array of pairwise t tests toward more general linear modeling structures, such as those provided by the extendable ANOVA framework. In this Perspective, we present arguments for making this transition and illustrate how it will help to avoid incorrect conclusions in factorial interaction studies (genotype × genotype, genotype × treatment, and treatment × treatment, or higher levels of interaction) that are becoming more prevalent in this new era of plant biology.

PMID:
26220933
PMCID:
PMC4568503
DOI:
10.1105/tpc.15.00238
[Indexed for MEDLINE]
Free PMC Article

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