A Method To Assess Significance Of Differences In RNA Expression Levels Among Specific Groups Of Genes

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.