Seeing the microbiome through a host lens

Sean recently published a commentary in the journal mSystems that outlines a vision of defining ‘microbiome health’ through a host lens: i.e. determining what exact components of the variation in the microboita influence host phenotypes. Much of the variation in the microbiome likely has nothing to do with the health state of the host, but loss/gain of critical diversity and/or functionality can have a major impact on host health. To…

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Correcting Batch Effects in Microbiome Data

Batch Effects in 16S Datasets Complicate Cross-Study Comparisons High-throughput data generation platforms, like mass-spectrometry, microarrays, and second-generation sequencing are susceptible to batch effects due to run-to-run variation in reagents, equipment, protocols, or personnel. Currently, batch correction methods are not commonly applied to microbiome sequencing datasets. In this paper, we compare different batch-correction methods applied to microbiome case-control studies. We introduce a model-free normalization procedure where features (i.e. bacterial taxa) in…

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