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Estimation of the coverage provided by a metagenomic data set, i.e., what fraction of the microbial community was sampled by DNA sequencing, represents an essential first step of every culture-independent genomic study that aims to robustly assess the sequence diversity present in a sample. However, estimation of coverage remains elusive because of several technical limitations associated with high computational requirements and limiting statistical approaches to quantify diversity. Here we described Nonpareil 3, a new bioinformatics algorithm that circumvents several of these limitations and thus can facilitate culture-independent studies in clinical or environmental settings, independent of the sequencing platform employed. In addition, we present a new metric of sequence diversity based on rarefied coverage and demonstrate its use in communities from diverse ecosystems.
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Luis M. Rodriguez‐R
Santosh Gunturu
James M. Tiedje
mSystems
Michigan State University
Georgia Institute of Technology
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Rodriguez‐R et al. (Wed,) studied this question.
www.synapsesocial.com/papers/69ff8e0cef8139f8ff77641f — DOI: https://doi.org/10.1128/msystems.00039-18