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Isolation and Analysis of Microbial Communities in Soil, Rhizosphere, and Roots in Perennial Grass Experiments
Published on: July 24, 2018
The microgeo: an R package rapidly displays the biogeography of soil microbial community traits on maps
Chaonan Li1, Chi Liu2, Hankang Li3
1Ecological Security and Protection Key Laboratory of Sichuan Province, Mianyang Normal University, Mianyang 621000, China.
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.
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