In addition to the pre-loaded maps, we documented the workflow and functions for plant researchers to create their own ggPlantmap. The creation of new ggPlantmaps is based on the manual segmentation of plant shapes into distinct Regions of Interest (ROIs) using the open-source software for image analysis Icy (De Chaumont et al., 2012). With our described method, users can generate new ggPlantmaps without the necessity of high-resolution images and advanced coding skills. The ggPlantmap package is an open-source project, encouraging community contributions and creation of maps that will be continuously loaded into the package. We encourage users to extend its functionality to meet specific research requirements and to better display plant biological data. Its compatibility with R, one of the most comprehensive programing languages in plant biology, makes it a versatile and accessible tool for the plant science community.
Statement of Need
Understanding the spatial distribution of gene expression patterns or any other quantitative data within plant tissues and cells is fundamental to understand the complex and intricate events in plant biology. The Plant eFP (Expression, Function, and Protein Localization) Browser (Winter et al., 2007) has been an extremely valuable resource for researchers seeking to visualize gene expression data in the context of plant tissues across many different plant species (Winter et al., 2007). Although widely used by the plant research community, the Plant eFP browser 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 incorporate their own spatial quantitative data or explore specific aspects of gene expression within plant tissues. To address this issue, we created ggPlantmap to allow plant researchers to create ggplot maps from plant images, like the Plant eFP Browser, with minimal knowledge in the R language (Figure 3). In this sense, ggPlantmap can play an important role in the plant science toolbox by offering an open, accessible, and customizable solution for creating quantitative image maps from plant images. By providing researchers with the means to independently generate maps from plant images, we aim to empower plant scientists to explore the visualization and communication of plant research in creative and exciting ways. We hope that ggPlantmap can assist the plant science community, fostering innovation and improving our understanding of plant development and function.