Giovanni Santacatterina

This paper introduces a Bayesian framework for differential gene expression analysis that scales to over 10 million cells and integrates data from multiple patients.

This paper introduces SCOUT, a synthetic whole-genome sequencing resource for benchmarking cancer genomic analysis, revealing performance issues in complex tumours and highlighting the importance of evolutionary ground truth.

The paper introduces ctDNAmer, a reference-free tool for detecting ctDNA from WGS data by analyzing k-mers, showing improved tumor fraction estimation and detection compared to traditional methods.

This paper introduces TickTack, a Bayesian model to time and cluster co-occurring genome amplifications in cancer, revealing insights into tumor evolution and genomic instability.

This paper introduces a Bayesian framework to predict tumour evolution and drug resistance using longitudinal cancer data across three cancer types.