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Title: Insights into study design and statistical analyses in translational microbiome studies DOI:10.21037/atm.2017.01.13 Abstract & Authors：展开 Abstract:Research questions in translational microbiome studies are substantially more complex than theircounterparts in basic science. Robust study designs with appropriate statistical analysis frameworks are pivotal tothe success of these translational studies. This review considers how study designs can account for heterogeneousphenotypes by adopting representative sampling schemes for recruiting the study population and making carefulchoices about the control population. Advantages and limitations of 16S profiling and whole-genome sequencing,the two primary techniques for measuring the microbiome, are discussed followed by an overview of bioinformaticprocessing of high-throughput sequencing data from these measurements. Practical insights into the downstreamstatistical analyses including data processing and integration, variable transformations, and data exploration areprovided. The merits of regularization and ensemble modeling for analyzing microbiome data are discussedalong with a recommendation for selecting modeling approaches based on data-driven simulations and objectiveevaluation. The review builds on several recent discussions of study design issues in microbiome research but witha stronger emphasis on the downstream and often-ignored aspects of statistical analyses that are crucial for bridgingthe gap between basic science and translation. All Authors:Jyoti Shankar First Authors:Jyoti Shankar Correspondence:Jyoti Shankar |
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