Shotgun metagenomics, from sampling to analysis
By Christopher Quince, A. Walker, Jared T. Simpson, Nicholas J. Loman, Nicola Segata. Nature Biotechnology, 2017
1,703 citations recorded by the source corpus.
Subfields: Ecology, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/e99a52affca0fa0cab59c3a5ae5c02eb9752e5d7
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Ecology
- Curtis Huttenhower
- Florian P. Breitwieser
- Steven L. Salzberg
- Nicola Segata
- Nikos Kyrpides
- Dominik G. Grimm
- Richa Bharti
- Daniel N. Baker
In Molecular Biology
- Curtis Huttenhower
- Nicola Segata
- Florian P. Breitwieser
- Steven L. Salzberg
- Eric A. Franzosa
- Dominik G. Grimm
- Edoardo Pasolli
- Richa Bharti
Citations in the corpus
- Microbial Biodiversity and Bioremediation Assessment Through Omics Approaches (2020, methodology): “The widely accepted technique for decontaminating a polluted environment in an eco-friendly and sustainable manner is bioremediation (Paul et al., 2005; Raghunandan et al., 2018).”
- MetaWRAP—a flexible pipeline for genome-resolved metagenomic data analysis (2018, background): “WMG shotgun sequencing reads from hundreds to thousands of community members generate unique challenges for data analysis and interpretation [3, 7].”
- SCycDB: A curated functional gene database for metagenomic profiling of sulphur cycling pathways (2020, background): “The development of shotgun metagenome sequencing approaches has provided new insights into our understanding of biogeochemical cycling in natural ecosystems (Knight et al., 2018; Nayfach & Pollard, 2016; Quince et al., 2017; Sharpton, 2014).”
- Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3 (2020, background): “16S rRNA gene) sequencing, as well as functional profiling of genes or biochemical pathways (Morgan et al., 2013; Quince et al., 2017; Segata et al., 2013).”
- IMG/M v.5.0: an integrated data management and comparative analysis system for microbial genomes and microbiomes (2018, background): “Genomeresolved metagenomics has become a powerful approach in microbiome research to link metabolic and functional potential with phylogenetic information, providing genomic context for uncultivated microbes (38).”
- KrakenUniq: confident and fast metagenomics classification using unique k-mer counts (2018, background): “Assembly-based methods also help to avoid false positives, but these are useful only for highly abundant species [8].”
- A practical guide to amplicon and metagenomic analysis of microbiome data (2020, background): “For a more comprehensive review on metagenomic experiments and analysis, we recommend Quince et al. (2017).”