BEKVAEM: INTEGRATIVE DATA EXPLORER FOR HI-C DATA

Main Article Content

Andreas Hofmann
Jan Müggenburg
Frédéric Crémazy
Dieter W. Heermann

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: https://heidata.uni-heidelberg.de/privateurl.xhtml?token=f4a058b3-7020-4002-902d-96bab5fbe9b1


A demonstration server is available at http://pi306a.itp.uni-heidelberg.de/bekvaem

Article Details

How to Cite
HOFMANN, Andreas et al. BEKVAEM: INTEGRATIVE DATA EXPLORER FOR HI-C DATA. Journal of Bioinformatics and Genomics, [S.l.], n. 2 (11), sep. 2019. ISSN 2530-1381. Available at: <http://journal-biogen.org/article/view/166>. Date accessed: 11 nov. 2019. doi: http://dx.doi.org/10.18454/jbg.2019.2.11.1.
Section
Novel computational tools and databases
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