Complementary computational methods reveal novel gene program changes
During a recent session of the COSBI Internal Talks, Filippo Gastaldello presented new developments from our ongoing research on Idiopathic Pulmonary Fibrosis (IPF), a complex and still poorly understood lung disease characterized by progressive tissue scarring.
The work focuses on leveraging single-cell transcriptomic data to dissect the landscape of gene program deregulation in IPF. By integrating differential expression analyses with matrix factorization-based methods, the study aims to identify coordinated changes in gene activity across specific cell populations, providing a more nuanced view of disease-associated molecular mechanisms.
A key message emerging from the presentation is the importance of methodological complementarity. Classical approaches and more advanced techniques, such as Spectra-based methods, offer distinct but overlapping insights. Their combined use—and, crucially, the cross-validation of results between methods—is essential to robustly identify and interpret novel gene program alterations.
Building on these findings, the next phase of the project will focus on gene network analysis. This will enable the identification of key interactors and shared regulatory mechanisms, with the ultimate goal of supporting targeted drug repurposing strategies in IPF.
These findings further support the role of integrative computational approaches in the study of complex diseases.
