Abstract
Recent advancements in DNA sequencing capacity have resulted in a flood of metagenomic data being generated, together with a myriad of computational tools for metagenomic analysis. Selecting the right tools in this jungle of options can be hard, particularly as new developments are presented almost daily. This chapter provides an overview of recent software for metagenomic analysis, discussing different strategies to perform taxonomic classification, functional analysis, metagenomic assembly, and statistical comparisons between metagenomes. The chapter also considers the use of automated computational “pipelines” for analysis of metagenomic data and highlights their pros and cons in comparison to running the analyses one by one. Currently, it is hard to point out any tools that obviously perform better in every situation, but there are certain analysis strategies that clearly should be avoided. Those are highlighted in this chapter, and instead robust and well-functioning software tools that can be used are suggested.
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