Hoang, Van L.T.Tom, Lisa N.Quek, Xiu-ChengTan, Jean-MariePayne, Elizabeth J.Lin, Lynlee L.Sinnya, SudiptaRaphael, Anthony P.Lambie, DuncanFrazer, Ian H.Dinger, Marcel E.Soyer, H. PeterProw, Tarl W.2017-11-212017Hoang, V. L., L. N. Tom, X. Quek, J. Tan, E. J. Payne, L. L. Lin, S. Sinnya, et al. 2017. “RNA-seq reveals more consistent reference genes for gene expression studies in human non-melanoma skin cancers.” PeerJ 5 (1): e3631. doi:10.7717/peerj.3631. http://dx.doi.org/10.7717/peerj.3631.http://nrs.harvard.edu/urn-3:HUL.InstRepos:34375065Identification of appropriate reference genes (RGs) is critical to accurate data interpretation in quantitative real-time PCR (qPCR) experiments. In this study, we have utilised next generation RNA sequencing (RNA-seq) to analyse the transcriptome of a panel of non-melanoma skin cancer lesions, identifying genes that are consistently expressed across all samples. Genes encoding ribosomal proteins were amongst the most stable in this dataset. Validation of this RNA-seq data was examined using qPCR to confirm the suitability of a set of highly stable genes for use as qPCR RGs. These genes will provide a valuable resource for the normalisation of qPCR data for the analysis of non-melanoma skin cancer.en-USRNA-seqReference geneqPCRNon-melanoma skin cancerJournal Article2017-11-2110.7717/peerj.3631