Algorithms for Structural Variation Analysis in Challenging Genomic Regions

Structural variations are genomic alterations affecting portions of the chromosomes longer than 50 base pairs. These alterations are a main contributing factor to human diseases and different types of cancer.

The main limitation of current approaches for the analysis of structural variations lies in their unreliability in characterizing these alterations in repetitive and hard-to-call regions of the genome.

Structural variations falling in these regions can not be routinely detected and their significance is still unknown.In this proposal, we aim to develop novel computational approaches to address the challenge of fully characterizing structural variations in these hard and still uninvestigated regions.

By developing accurate tools for comprehensive detection of structural variations, we aim to increase our current knowledge of this class of genetic alterations.

Moreover, by designing new benchmarking methodologies, we will provide a more accurate evaluation of our as well as other tools.

This will also assist the development of new generations of tools able to accurately characterize structural variations that are currently unknown.We will employ a multi-faceted strategy that is not limited to a single sequencing technology.

By combining data coming from different sequencing technologies and ideas coming from alignment-based, assembly-based, mapping-free, and pangenomic-based approaches, we will be able to take a significant step towards the complete characterization and analysis of structural variations.The development of new tools and the planned collaboration with biology-oriented research groups will enhance our understanding of the impact of structural variations on human health, diseases, and cancer and hence improve clinical diagnostics and pave the way for personalized medicine.