Accessible pipeline for translational research using TCGA: Examples of relating gene mechanism to disease-specific outcomes

Abstract

Bioinformatic scientists are often asked to do widespread analyses of publicly available datasets in order to identify genetic alterations in cancer for genes of interest; therefore, we sought to create a set of tools to conduct common statistical analyses of The Cancer Genome Atlas (TCGA) data. These tools have been developed in response to requests from our collaborators to ask questions, validate findings, and better understand the function of their gene of interest. We describe here what data we have used, how to obtain it, and what figures we have found useful.