Abstract
User-friendly computational tools for 16S ribosomal RNA (rRNA) sequencing analysis enable researchers who are not bioinformaticians to analyze and interpret sequencing data from microbial communities. These tools' easy-to-use interfaces belie the sophisticated and rapidly-evolving science of their underlying algorithms. When analyzing 16S data from a simple microbiome experiment, we found that superficially unimportant decisions about the bioinformatic pipeline led to results with radically different biological interpretations. We share these results as a cautionary tale whose moral is that, in 16S analysis, the devil is in the details. Wet bench researchers should therefore strongly consider partnering with bioinformaticians or computational biologists when analyzing 16S data.