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