Abstract
Recent studies on microbiome highlighted their importance
in various environments including human, where they are
involved in multiple biological contexts such as immune mechanism,
drug response, and metabolism. The rapid increase
of new findings in microbiome research is partly due to the
technological advances in microbiome identification, including
the next-generation sequencing technologies. Several applications
of different next-generation sequencing platforms
exist for microbiome identification, but the most popular method
is using short-read sequencing technology to profile targeted
regions of 16S rRNA genes of microbiome because of
its low-cost and generally reliable performance of identifying
overall microbiome compositions. The analysis of targeted
16S rRNA sequencing data requires multiple steps of data processing
and systematic analysis, and many software tools have
been proposed for such procedures. However, properly organizing
and using such software tools still require certain
level of expertise with computational environments. The purpose
of this article is introducing the concept of computational
analysis of 16S rRNA sequencing data to microbiologists
and providing easy-to-follow and step-by-step instructions
of using recent software tools of microbiome analysis.
This instruction may be used as a quick guideline for general
next-generation sequencing-based microbiome studies or a
template of constructing own software pipelines for customized
analysis.
Citations
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