With the increasing availability of big data in every field of science, the development of visual collecting tools able to simplify the interpretation of such quantity of data is essential. However, many scientists do not have a specific concept of data visualization, manifesting serious problems in implementing it, especially for omics data. Thus, bioinformatics specialists continuously develop new algorithms and tools to perform the deepest analysis of these data, along with innovative methods to simplify their output representation.
In this work, we evaluated a set of free tools that we considered highly suitable for enhancing the interpretation of next-generation sequencing analysis outcomes, above all regarding exomic and transcriptomic experiments.
Visualization of both kinds of omics data is frequently employed in biomedical research to access knowledge within a genomic context, to communicate, and to explore datasets to elaborate well-defined hypotheses. To realize this purpose, it is necessary to adopt dedicated algorithms and tools specific for each kind of analysis.
Circos and VIsualization of VAriants (VIVA) tools allowed us a straightforward, summarized representation of exomic outcomes, while the Omics Playground platform produced powerful results from RNA-Seq analyses. Finally, both omics sources represented the input of pathway analysis by ClueGO and CluePedia tools, which produced enriched network maps useful to discover novel insights from obtained data.
Today, a huge variety of visualization tools is available to data scientists and it can be difficult to select the right one. Data visualization users should, thus, mainly focus their choice on ease of use and whether a tool has the features they need.
