Francesco Ferrari, PhD
Principal Investigator
FIRC Institute of Molecular Oncology
Extracting information on multiscale chromatin organization from Hi-C data
Hi-C experiments provide data matrices with interaction frequencies for potentially any pair of genomic loci. Extracting biologically meaningful information out of these data matrices involve several computationally challenging tasks.
A first challenge is due to the lack of consensus on the data analysis procedures and best practices. This is a consequence of the fast-evolving speed of this field.
A second problem is that data analysis approaches are commonly designed to extract information on either i) chromatin point interactions or ii) the structural compartmentalization of chromatin. However, from a biological point of view, this dichotomous approach can be limiting. Indeed, there’s a wide range of unanswered questions about the role of chromatin 3D organization in regulating genome functionality that will demand alternative solutions.
Finally, the increase in data resolution is requiring new tools to efficiently handle large data matrices, while at the same time allowing users to extract biologically meaningful information at multiple scales.
I will discuss my group latest work concerning these computational challenges. In particular the review how new data analyses solutions have been instrumental to address specific biological questions.
