Comparison of expression data requires normalization. The optimum normalization method depends on sample type. The most common method is to normalize to reference genes. It is critical to select appropriate reference genes and validate them, but there are cases when one fails to identify suitable genes for normalization and must use alternatives. There are cases when normalization of a target gene’s expression to another gene’s expression is most unsuitable. In this lecture, we will learn the goals of normalization and how to select the best normalization strategy.
Mikael Kubista
TATAA Biocenter
Professor
Kubista is one of the pioneers in molecular diagnostics. He invented the light-up probes, which led to the foundation of LightUp Technologies AB as Europe´s first company focusing on qPCR based diagnostics. He co-founded MultiD Analyses AB, which develops the market leading qPCR analysis software GenEx. In 2001 Kubista set up the TATAA Biocenter as center of excellence in qPCR and gene expression analysis. TATAA biocenter was the first laboratory in Europe to obtain flexible ISO 17025 accreditation and was presented the Frost & Sullivan Award for Customer Value Leadership as Best-in-Class Services for Analyzing Genetic Material in 2013. In 2014 TATAA introduced non-invasive prenatal testing (NIPT) in Sweden founding Life Genomics AB. Kubista also co-authored the MIQE guidelines and he is member of the CEN/ISO working groups developing guidelines for the pre-analytical process in molecular diagnostics. Most recently Kubista’s team invented Two-tailed PCR, which is currently the most sensitive and specific method for microRNA analysis. Since 2007 Kubista heads the Department of Gene Expression at the institute of Biotechnology of the Czech Academy of Sciences.
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