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ggPlantmap: an open-source R package for the creation of informative and quantitative ggplot maps derived from plant images.

Leonardo JoKaisa Kajala
Published in: Journal of experimental botany (2024)
As plant research generates an ever-growing volume of spatial quantitative data, the need for decentralized and user-friendly visualization tools to explore large and complex datasets tools becomes crucial. Existing resources, such as the Plant eFP (electronic Fluorescent Pictograph) viewer, have played a pivotal role on the communication of gene expression data across many plant species. However, although widely used by the plant research community, the Plant eFP viewer lacks open and user-friendly tools for the creation of customized expression maps independently. Plant biologists with less coding experience can often encounter challenges when attempting to explore ways to communicate their own spatial quantitative data. We present 'ggPlantmap' an open-source R package designed to address this challenge by providing an easy and user-friendly method for the creation of ggplot representative maps from plant images. ggPlantmap is built in R, one of the most used languages in biology to empower plant scientists to create and customize eFP-like viewers tailored to their experimental data. Here, we provide an overview of the package and tutorials that are accessible even to users with minimal R programming experience. We hope that ggPlantmap can assist the plant science community, fostering innovation and improving our understanding of plant development and function.
Keyphrases
  • gene expression
  • healthcare
  • big data
  • mental health
  • public health
  • poor prognosis
  • machine learning
  • long non coding rna
  • low cost
  • minimally invasive
  • plant growth
  • single molecule