Post hoc survival analyses using RNAseq data: handle with care

With the advent of next-generation sequencing technologies, there has been a dramatic increase in the availability of paired clinical and transcriptomic data in a variety of disease states. For basic science researchers, this has provided a valuable opportunity for querying the impact of the transcript levels of a gene on disease survival in humans. However, there are a multitude of methodological and technical considerations to evaluate before embarking on these analyses. Herein, we provide a brief description of statistical considerations involved in these analyses, geared toward basic scientists who may not necessarily routinely use such statistical models as part of their studies.

Automated summary

With the advancement of next-generation sequencing technologies, more clinical and transcriptomic data are available for studying disease states. This provides an opportunity for basic science researchers to explore the impact of gene transcript levels on disease survival in humans. However, careful evaluation of statistical considerations and technical factors is necessary before conducting these analyses. In this article, we provide a brief description of the statistical considerations involved in such analyses, specifically targeting basic scientists who may not have extensive experience with statistical models.