Abstract
Abstract
Microbiome research has grown rapidly over the past decade, with a proliferation of new methods that seek to make sense of large, complex data sets. Here, we survey two of the primary types of methods for analyzing microbiome data: read classification and metagenomic assembly, and we review some of the challenges facing these methods. All of the methods rely on public genome databases, and we also discuss the content of these databases and how their quality has a direct impact on our ability to interpret a microbiome sample.
Funder
National Institute of General Medical Sciences
National Human Genome Research Institute
Publisher
Oxford University Press (OUP)
Subject
Molecular Biology,Information Systems
Cited by
385 articles.
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