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Nucleic Acids as Molecular Diagnostics, p. 241-270

DOI: 10.1002/9783527672165.ch11

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Towards the Identification of Condition-Specific Microbial Populations from Human Metagenomic Data

Journal article published in 2014 by Cédric C. Laczny ORCID, Paul Wilmes
This paper is available in a repository.
This paper is available in a repository.

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Data provided by SHERPA/RoMEO

Abstract

Mixed microbial communities are ubiquitous and contribute essential functionalities to all ecosystems. Interindividual differences in terms of either microbiome composition and/or functional potential have been described using high-throughput metagenomics sequencing data. This chapter considers why culture-independent approaches are desirable and discusses various aspects of DNA-based characterization of entire microbial communities for the detection of specific microorganisms relevant to human health and disease, without the need to subject samples to known cultivation bottlenecks. The deconvolution of microbial community composition plays an essential role for the identification of condition-specific microbial populations from human metagenomic data. The chapter highlights recent human microbiome-focused studies that have employed a subset of available metagenomic data analysis tools for the resolution of the taxonomic structure and/or functional analysis of community members. These tools can generally be divided into reference-dependent approaches relying on prior knowledge or reference-independent approaches.