The aim of our work was to show how a chosen normal-isation strategy can affect the outcome of quantitative gene expression studies. As an example, we analysed the expression of three genes known to be upregulated under hypoxic conditions: HIF1A, VEGF and SLC2A1 (GLUT1). Raw RT-qPCR data were normalised using two different strategies: a straightforward normalisation against a single reference gene, GAPDH, using the 2(-ΔΔCt) algorithm and a more complex normalisation against a normalisation factor calculated from the quantitative raw data from four previously validated reference genes. We found that the two different normalisation strategies revealed contradicting results: normalising against a validated set of reference genes revealed an upregulation of the three genes of interest in three post-mortem tissue samples (cardiac muscle, skeletal muscle and brain) under hypoxic conditions. Interestingly, we found a statistically significant difference in the relative transcript abundance of VEGF in cardiac muscle between donors who died of asphyxia versus donors who died from cardiac death. Normalisation against GAPDH alone revealed no upregulation but, in some instances, a downregulation of the genes of interest. To further analyse this discrepancy, the stability of all reference genes used were reassessed and the very low expression stability of GAPDH was found to originate from the co-regulation of this gene under hypoxic conditions. We concluded that GAPDH is not a suitable reference gene for the quantitative analysis of gene expression in hypoxia and that validation of reference genes is a crucial step for generating biologically meaningful data.