gganatogram: An R package for modular visualisation of anatograms and tissues based on ggplot2 Journal Article


Author: Maag, J. L. V.
Article Title: gganatogram: An R package for modular visualisation of anatograms and tissues based on ggplot2
Abstract: Displaying data onto anatomical structures is a convenient technique to quickly observe tissue related information. However, drawing tissues is a complex task that requires both expertise in anatomy and the arts. While web based applications exist for displaying gene expression on anatograms, other non-genetic disciplines lack similar tools. Moreover, web based tools often lack the modularity associated with packages in programming languages, such as R. Here I present gganatogram, an R package used to plot modular species anatograms based on a combination of the graphical grammar of ggplot2 and the publicly available anatograms from the Expression Atlas. This combination allows for quick and easy, modular, and reproducible generation of anatograms. Using only one command and a data frame with tissue name, group, colour, and value, this tool enables the user to visualise specific human and mouse tissues with desired colours, grouped by a variable, or displaying a desired value, such as gene-expression, pharmacokinetics, or bacterial load across selected tissues. I hope that this tool will be useful by the wider community in biological sciences. Community members are welcome to submit additional anatograms, which can be incorporated into the package. A stable version gganatogram has been deposited to neuroconductor, and a development version can be found on github/jespermaag/gganatogram.
Keywords: anatomy; tissues; organs; r; anatograms; expression atlas; ggplot2
Journal Title: F1000Research
Volume: 7
ISSN: 2046-1402
Publisher: Science Navigation Group  
Date Published: 2018-09-28
Start Page: 1576
Language: English
DOI: 10.12688/f1000research.16409.1
PROVIDER: scopus
PMCID: PMC6208569
PUBMED: 30467523
DOI/URL:
Notes: Updated version available, see DOI: 10.12688/f1000research.16409.2 -- F1000Res -- Export Date: 2 January 2019 -- Article -- Source: Scopus C2 - 30467523
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  1. Jesper Lars Viktor Maag
    14 Maaaag