GAC

GAC is a software tool that provides a web-based suite for interactive visualization of clinical associations using high-dimensional data, such as gene expression, combined with clinical data. The tool is based on supervised principal component analysis (SuperPC), an approach that uses both high-dimensional data and clinical data to infer clinical associations.

The approach has been extended to address binary outcomes, in addition to continuous and time-to-event data, thereby increasing the use and flexibility of SuperPC. The tool also offers an interactive visualization for summarizing results based on a forest plot for binary and time-to-event data.

One of the primary advantages of GAC is that it provides a one-stop-shop for conducting statistical analysis to identify and visualize the association between a clinical outcome of interest and high-dimensional data types, such as genomic data.