Antonio Colaprico

The paper introduces Moonlight2, an updated framework that uses mutation-based mechanistic indicators to identify driver genes in cancer, applied to Basal-like breast cancer.

The paper introduces new features in the TCGAbiolinks R/Bioconductor package to improve cancer data analysis, including better differential expression analysis, tumor purity estimation, and integration of normal samples from GTEx.

TCGAbiolinksGUI provides a graphical interface for analyzing GDC cancer data, making the TCGAbiolinks package more accessible to non-R users.

Moonlight identifies cancer driver genes and their roles by integrating functional analysis and gene regulatory networks from expression data, distinguishing tumor suppressors, oncogenes, and moonlight genes.