Visual Exploratory Data Analysis for Copy Number Variation Studies in Biomedical Research

Chiara Vischioni, Fabio Bove, Federica Mandreoli, Riccardo Martoglia, Valentino Pisi, Cristian Taccioli

Abstract: The study of Copy Number Variations (CNVs) is recently emerging as a hot topic for biomedical cancer research. While different data sources, websites, and tools concerning genomic CNVs have been made publicly available, CNV data is still a largely unexplored source of biological information, due to the limitations of currently available analysis tools. To this respect, we propose a novel platform, named VarNuCopy, that overcomes such limitations by pursuing the core principles of Exploratory Data Analysis (EDA) in the context of Copy Number Variation (CNV) data. The platform has been made publicly available as a web application, and is, to our best knowledge, the first tool enabling visual, interactive exploration and analysis of the CNV landscape of multiple species. Through novel client and server-side optimizations inspired by scalable data science, VarNuCopy implements a comprehensive and efficient data exploration solution that empowers researchers to easily recognize complex trends and patterns within a huge amount of data concerning CNVs, and to identify new target genes that might function as tumor suppressor and oncogenes.