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Use and abuse of correlation analyses in microbial ecology

The ISME Journal, 2019-11, Vol.13 (11), p.2647-2655 [Peer Reviewed Journal]

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Title:
Use and abuse of correlation analyses in microbial ecology
Author: Carr, Alex ; Diener, Christian ; Baliga, Nitin S ; Gibbons, Sean M
Subjects: Asymmetry ; Computational Biology - methods ; Correlation analysis ; Correlation of Data ; Covariance ; Ecological monitoring ; Ecology ; Ecosystem ; Environmental Microbiology ; Humans ; Hypotheses ; Microbial Interactions ; Microorganisms ; Microscopy ; Population ; Random variables ; Research methodology
Is Part Of: The ISME Journal, 2019-11, Vol.13 (11), p.2647-2655
Description: Correlation analyses are often included in bioinformatic pipelines as methods for inferring taxon-taxon interactions. In this perspective, we highlight the pitfalls of inferring interactions from covariance and suggest methods, study design considerations, and additional data types for improving high-throughput interaction inferences. We conclude that correlation, even when augmented by other data types, almost never provides reliable information on direct biotic interactions in real-world ecosystems. These bioinformatically inferred associations are useful for reducing the number of potential hypotheses that we might test, but will never preclude the necessity for experimental validation.
Publisher: England: Nature Publishing Group
Language: English
Identifier: ISSN: 1751-7362
EISSN: 1751-7370
DOI: 10.1038/s41396-019-0459-z
PMID: 31253856
Source: MEDLINE
PubMed Central
ProQuest Central

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