![]() Moreover, singular input image format and rudimentary text support hinder its usability. It fails to handle stylesheet conflicts caused by SVG files from different tools and lacks flexibility in design where images are required to overlay onto each other. Please note the unexpected black triangles generated by both tools and loss of green color in the text (e.g., DNA replication) by PowerPoint, while the same Scalable Vector Graphics (SVG) image is rendered perfectly by bioInfograph as shown in Figure 1D.Ī previously developed web-based plot designing tool, canvasDesigner ( Zhang et al., 2018), attempted to provide a solution but with limited success. But these tools either cannot deal with complex pathway diagrams in SVG format from WikiPathways, or render this format in low resolution with missing colors, sometimes even in malformed appearance as shown in Figure 2.Īn example of a pathway diagram from WikiPathways is not properly rendered by (A) Microsoft PowerPoint or (B) Inkscape. Biologists usually turn to user-friendly commercial tools, such as Microsoft PowerPoint, as viable options to arrange such plots. And often, such illustration is required to be in high resolution. Nevertheless, creating graphical abstracts like Figure 1 to give a high-level comprehensive story becomes a routine task in biological publication. To point out, these SVG images are rendered naturally by modern web browsers including Chrome, Firefox, Safari, and Microsoft Edge.Ĭomposing multi-panel publication-ready figures, such as the one presented in Figure 1, usually poses a challenge for biologists with no or modest programming skills after gathering individual plots from various sources in diversified formats, such as png, gif, jpg, tiff, pdf, and svg. In addition, SVG is usually set as the default image output by many JavaScript-based plotting libraries like D3 ( Bostock et al., 2011). This format has become one of the most broadly used image outputs adopted by many data analysis tools used by computational biologists, notably R ( Venables et al., 2002), ggplot2 ( Wickham, 2016), and numerous R and Bioconductor ( Gentleman et al., 2004) packages. SVG is an Extensible Markup Language (XML)-based vector image format, scalable to any resolution without blurry pixelization that happens in other popular image formats such as png, gif, and jpg. Popular computational biology databases such as Reactome ( Jassal et al., 2020), WikiPathways ( Martens et al., 2021), and visualization tools such as Coral ( Metz et al., 2018) and ComplexHeatmap ( Gu et al., 2016) often produce biological images in Scalable Vector Graphics (SVG) format. In the end, we make the online tool publicly available at while releasing the source code at under MIT open-source license. ![]() To highlight, the sharable interactive HTML output with zoom-in function is a unique feature not seen in any other similar tools. It solves stylesheet conflicts of coexisting SVG plots, integrates a rich-text editor, and allows creative design by providing advanced functionalities like image transparency, controlled vertical stacking of plots, versatile image formats, and layout templates. To address the challenge, we developed bioInfograph, a web-based tool that allows users to interactively arrange high-resolution images in diversified formats, mainly Scalable Vector Graphics (SVG), to produce one multi-panel publication-quality composite figure in both PDF and HTML formats in a user-friendly manner, requiring no programming skills. In addition, it is a time-consuming and sometimes frustrating process even for a computationally savvy scientist who frequently takes a trial-and-error iterative approach to get satisfactory results. ![]() However, assembling individual plots in different formats from various sources into one high-resolution figure in the desired layout requires mastery of commercial tools or even programming skills. Many fit-for-purpose bioinformatics tools generate plots to interpret complex biological data and illustrate findings.
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