Metagenomics - a guide from sampling to data analysis

TLDR

Metagenomics uses genomic technologies and bioinformatics to directly access the genetic content of entire microbial communities, driving advances in microbial ecology, evolution, and diversity and underscoring the need for standardized procedures as datasets grow. The review aims to summarize current opinions in metagenomics and offer practical guidance on sample processing, sequencing, assembly, binning, annotation, experimental design, statistical analysis, data storage, and sharing. It provides practical guidance on sample processing, sequencing technology, assembly, binning, annotation, experimental design, statistical analysis, data storage, and data sharing.

Abstract

Metagenomics applies a suite of genomic technologies and bioinformatics tools to directly access the genetic content of entire communities of organisms. The field of metagenomics has been responsible for substantial advances in microbial ecology, evolution, and diversity over the past 5 to 10 years, and many research laboratories are actively engaged in it now. With the growing numbers of activities also comes a plethora of methodological knowledge and expertise that should guide future developments in the field. This review summarizes the current opinions in metagenomics, and provides practical guidance and advice on sample processing, sequencing technology, assembly, binning, annotation, experimental design, statistical analysis, data storage, and data sharing. As more metagenomic datasets are generated, the availability of standardized procedures and shared data storage and analysis becomes increasingly important to ensure that output of individual projects can be assessed and compared.