There is an increasing need for rich and dynamic biological data visualizations in bioinformatic web applications. New standards in web technologies, like SVG or Canvas, are now supported by most modern web browsers allowing the blossoming of powerful visualizations in biological data analysis. The exploration of different ways to visualize genomic data is still challenging due to the lack of flexible tools to develop them. Here, I present a set of libraries aimed at creating powerful tree- and track-based visualizations for the web. Its modularity and rich API facilitate the development of many different visualizations ranging from simple species trees to complex visualizations comprising per-node data annotations or even simple genome browsers.