Mitochondria are ancient endosymbiotic organelles crucial to eukaryotic growth and metabolism. The mammalian mitochondrial genome encodes for 13 mitochondrial proteins, and the remaining mitochondrial proteins are encoded by the nuclear genome. Little is known about how coordination between the expression of the two sets of genes is achieved. Correlation analysis of RNA-seq expression data from large publicly available datasets is a common method to leverage genetic diversity to infer gene co-expression modules. Here we use this method to investigate nuclear-mitochondrial gene expression coordination. We identify a pitfall in correlation analysis that results from the large variation in the proportion of transcripts from the mitochondrial genome in RNA-seq data. Commonly used normalisation techniques based on total read counts, such as FPKM or TPM, produce artefactual negative correlations between mitochondrial- and nuclear-encoded transcripts. This also results in artefactual correlations between pairs of nuclear-encoded genes, with important consequences for inferring co-expression modules beyond mitochondria. We show that these effects can be overcome by normalizing using the median-ratio normalisation (MRN) or trimmed mean of M values (TMM) methods. Using these normalisations, we find only weak and inconsistent correlations between mitochondrial and nuclear-encoded mitochondrial genes in the majority of healthy human tissues from the GTEx database. We show that a subset of healthy tissues with high expression of NF-κB show significant coordination, suggesting a role for NF-κB in ensuring balanced expression between mitochondrial and nuclear genes. Contrastingly, most cancer types show robust coordination of nuclear and mitochondrial OXPHOS gene expression, identifying this as a feature of gene regulation in cancer.