Many research questions in plant science depend on surveys of the plant microbiome. When the questions depend on answering "who is there" rather than "what are they doing," the most cost-effective method for interrogating microbiomes is often via targeted meta-amplicon surveys. There are numerous platforms for processing and analyzing meta-amplicon data sets, but here we will look at a flexible, reproducible, and fully customizable pipeline in the R environment. This approach has the benefit of being able to process and analyze your data in the same setting, without moving back and forth between standalone platforms, and further benefits from being completely flexible in terms of analyses and visualizations you can produce, without being limited to pre-selected tools available in point-and-click analysis engines, such as QIIME, Galaxy, or MG-RAST.