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

DOI オープンアクセス

説明

<jats:title>ABSTRACT</jats:title><jats:p>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.</jats:p>

詳細情報 詳細情報について

  • CRID
    1874242817539606784
  • DOI
    10.1101/778043
  • データソース種別
    • OpenAIRE

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