Reference Genes for gene expression analysis in Head and Neck Squamous Cell Carcinoma: a Data Science Driven Approach

Abstract

Quantitative real time PCR (qPCR) remains by far the most cost-effective, fast yet sensitive technique to check the gene expression levels in various systems. Traditionally used reference genes over the years were found to be regulated heavily based on sample sources and/or experimental conditions. This paper therefore presents a data science driven -omic approach for selection of reference genes from ~60,000 candidates from The Cancer Genome Atlas (TCGA) and Broad Institute Cancer Cell Line Encyclopaedia (CCLE) for gene expression studies in head and neck squamous cell carcinoma (HNSCC).