Abstract
Motivation: The browser-based visualization of Hi-C contact maps alongside complementary data tracks is a computationally challenging task and requires an efficient software implementation to run on small clients. Few software packages have yet been shared with the community to address this problem and modification of these is cumbersome. Results: We introduce Bekvaem that addresses these problems by using high-level Python interfaces. Wrapping several libraries for online visualizations at the front-end and the organization of large biological data sets at the server-side allows for setting up a high-performance user-defined browser visualization for Hi-C data with just a few changes in the code. Availability and implementation: The source code, written in Python, of Bekvaem alongside its documentation and sample data is freely available on heiDATA . A demonstration server is available here .
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