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Understanding artificial mouse-microbiome heterogeneity and six actionable themes to increase study power

Authors :
Jun Miyoshi
Erika L. Moen
Danielle Kulpins
Betty Theriault
Alexander Rodriguez-Palacios
Alexandria LaSalla
Fabio Cominelli
Sanja Ilic
Gretchen Lam
Mark S. Sundrud
Abigail R. Basson
Publication Year :
2019
Publisher :
Cold Spring Harbor Laboratory, 2019.

Abstract

The negative effects of data clustering due to (intra-class/spatial) correlations are well-known in statistics to interfere with interpretation and study power. Therefore, it is unclear why housing many laboratory mice (≥4), instead of one-or-two per cage, with the improper use/reporting of clustered-data statistics, abound in the literature. Among other sources of ‘artificial’ confounding, including cyclical oscillations of the ‘cage microbiome’, we quantified the heterogeneity of modern husbandry practices/perceptions. The objective was to identify actionable themes to re-launch emerging protocols and intuitive statistical strategies to increase study power. Amenable for interventions, ‘cost-vs-science’ discordance was a major aspect explaining heterogeneity and the reluctance to change. Combined, four sources of information (scoping-reviews, professional-surveys, expert-opinion, and ‘implementability-score-statistics’) indicate that a six-actionable-theme framework could minimize ‘artificial’ heterogeneity. With a ‘Housing Density Cost Simulator’ in Excel and fully annotated statistical examples, this framework could reignite the use of ‘study power’ to monitor the success/reproducibility of mouse-microbiome studies.

Details

Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....07de6be793fe034b6d30d3f148eb3f34
Full Text :
https://doi.org/10.1101/778043