Ecological Security and Protection Key Laboratory of Sichuan Province, Mianyang Normal University, Mianyang 621000, China.
Engineering Research Center of Soil Remediation of Fujian Province University, College of Resources and Environment, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
FEMS Microbiol Ecol. 2024 Jun 17;100(7). doi: 10.1093/femsec/fiae087.
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.
许多 R 包提供了用于阐明土壤微生物多样性的统计方法,但它们仍然难以在地理地图上可视化微生物特征。这在解释区域尺度上的微生物生物地理学方面带来了挑战,特别是当空间尺度较大或采样点的分布不均匀时。在这里,我们开发了一个轻量级、灵活且用户友好的 R 包,称为 microgeo。该包集成了许多功能,包括读取、操作和可视化地理边界数据;下载空间数据集;以及使用基于网格的可视化、空间插值或机器学习计算微生物特征并将其渲染到地理地图上。使用这个 R 包,用户可以在地图上可视化任何由 microgeo 或其他工具计算出的特征,并可以结合从地理地图派生的元数据来分析微生物组数据。与其他用于统计分析微生物组数据的 R 包相比,microgeo 提供了更直观的方法来在大地理尺度上说明土壤微生物的生物地理学,是对统计驱动的比较的重要补充,并以更方便、更有效的方式促进了在大空间尺度上对公开可用的微生物组数据进行生物地理分析。microgeo R 包可以从 Gitee(https://gitee.com/bioape/microgeo)和 GitHub(https://github.com/ChaonanLi/microgeo)存储库安装。microgeo R 包的详细教程可在 https://chaonanli.github.io/microgeo 上获得。