Collection and implementation of gene expression signatures for cancer data interpretation

During the last decades, in literature, a variety of several types of gene expression signatures for the study of cancer biology have been described. These published signatures cover various aspects of tumor biology related to both cancer and normal cells present in the tumor microenvironment. Most of the proposed signatures lack a computational implementation that is fundamental for their usage and reproducibility. In the attempt of filling this gap of knowledge, during my thesis project, I worked on collecting existing gene expression signatures and providing a tool for their use in genomic data analysis. My contribution in this project has been collected in a new R package, called signifinder. Signifinder offers a unique tool to allow the use and comparison of different signatures within and between samples, also providing utilities for the graphical exploration of results.