Abstract
Most expression studies measure transcription rates across multiple conditions followed by clustering and functional enrichment. This enables discovery of shared function for differentially expressed genes, but is not useful for determining whether pre-defined groups of genes share or diverge in their expression patterns. Here we present a simple data transformation method that allows Gaussian parametric statistical analysis of expression for groups of genes, thus enabling a biologically relevant hypothesis-driven approach to gene expression analysis.
Copyright
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Posted May 12, 2017.
A method to assess significant differences in RNA expression among specific gene groups
