The HTPmod Shiny application enables modeling and visualization of large-scale biological data.

Chen D*, Fu LY, Hu D, Klukas C, Chen M, Kaufmann K
Commun Biol. 2018 Jul 5;1:89. doi: 10.1038/s42003-018-0091-x.

The wave of high-throughput technologies in genomics and phenomics are enabling data to be generated on an unprecedented scale and at a reasonable cost. Exploring the large-scale data sets generated by these technologies to derive biological insights requires efficient bioinformatic tools. Here we introduce an interactive, open-source web application (HTPmod) for high-throughput biological data modeling and visualization. HTPmod is implemented with the Shiny framework by integrating the computational power and professional visualization of R and including various machine-learning approaches. We demonstrate that HTPmod can be used for modeling and visualizing large-scale, high-dimensional data sets (such as multiple omics data) under a broad context. By reinvestigating example data sets from recent studies, we find not only that HTPmod can reproduce results from the original studies in a straightforward fashion and within a reasonable time, but also that novel insights may be gained from fast reinvestigation of existing data by HTPmod.

Cover image


School of Life Sciences, Nanjing University
Nanjing 210023, China

Back to top