Abstract
Many R packages provide statistical approaches for elucidating the diversity of soil microbes, yet they still struggle to visualize microbial traits on a geographical map. This creates challenges in interpreting microbial biogeography on a regional scale, especially when the spatial scale is large or the distribution of sampling sites is uneven. Here, we developed a lightweight, flexible, and user-friendly R package called microgeo. This package integrates many functions involved in reading, manipulating, and visualizing geographical boundary data; downloading spatial datasets; and calculating microbial traits and rendering them onto a geographical map using grid-based visualization, spatial interpolation, or machine learning. Using this R package, users can visualize any trait calculated by microgeo or other tools on a map and can analyze microbiome data in conjunction with metadata derived from a geographical map. In contrast to other R packages that statistically analyze microbiome data, microgeo provides more-intuitive approaches in illustrating the biogeography of soil microbes on a large geographical scale, serving as an important supplement to statistically driven comparisons and facilitating the biogeographic analysis of publicly accessible microbiome data at a large spatial scale in a more convenient and efficient manner. The microgeo R package can be installed from the Gitee (https://gitee.com/bioape/microgeo) and GitHub (https://github.com/ChaonanLi/microgeo) repositories. Detailed tutorials for the microgeo R package are available at https://chaonanli.github.io/microgeo.