Abstract
Microbiome datasets have expanded rapidly in recent years. Advances in DNA sequencing, as well as the rise of shotgun metagenomics and metabolomics, are producing datasets that exceed the ability of researchers to analyze them on their personal computers. Here we describe what Big Data is in the context of microbiome research, how this data can be transformed into knowledge about microbes and their functions in their environments, and how the knowledge can be applied to move microbiome research forward. In particular, the development of new high-resolution tools to assess strain-level variability (moving away from OTUs), the advent of cloud computing and centralized analysis resources such as Qiita (for sequences) and GNPS (for mass spectrometry), and better methods for curating and describing “metadata” (contextual information about the sequence or chemical information) are rapidly assisting the use of microbiome data in fields ranging from human health to environmental studies.
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