Pan-cancer analysis of prognostic genes This publication uses publicly available TCGA clinical and RNA-SEQ data to investigate prognostic genes in 16 different cancers. Multivariate Cox regression was used to identify each gene's correlation with survival. For many of the cancers in this study this is the first time RNA-SEQ data has been used to identify prognostic genes. This is also the first time that lists of all the correlations to survival have been made publicly available, providing cancer biologists with genes that may be involved in cancer, and computational biologists lists for identifying common pathways or patterns. All of the code for performing Cox regressions on these data sets is made available, allowing for adaptation to other cancers or a change in the Cox model. In fact, all the code necessary to reproduce every figure and table in this publication is available at my GitHub page: To learn more about this project, including its conceptualization and how to reproduce the work, follow the links below.
Project origins In this post I describe what necessitated this project, and how the project began. Read the post here
What was done in this study In this post I go into detail about the data and methods used in this publication. Read the post here
How to use the GitHub repository In this post I briefly show how to download and use the GitHub repository. Read the post here