Normalization strategies for mRNA expression data in cartilage research

Normalization strategies for real-time expression data in Chlamydia trachomatis.

Chlamydia trachomatis is a widespread obligate intracellular pathogen genetically non-tractable for which transcriptomics is a fundamental tool to better understand its biology. However, the suitability of endogenous controls for normalization of transcriptomic data in this bacterium still needs validation. We aimed to assess the stability of 10 genes for their potential use as endogenous contr...

Data Normalization Strategies for MicroRNA Quantification.

BACKGROUND Different technologies, such as quantitative real-time PCR or microarrays, have been developed to measure microRNA (miRNA) expression levels. Quantification of miRNA transcripts implicates data normalization using endogenous and exogenous reference genes for data correction. However, there is no consensus about an optimal normalization strategy. The choice of a reference gene remains...

cDNA Microarray Data Normalization

Applying Data-Driven Normalization Strategies for qPCR Data Using Bioconductor

High-throughput real-time quantitative reverse transcriptase polymerase chain reaction (qPCR) is a widely used technique in experiments where expression patterns of genes are to be profiled. qPCR is widely accepted as the ”gold standard” for analysis of gene expression. Recent technological advances have greatly expanded the total number of genes that can be analyzed in a single assay; qPCR exp...

RUV for normalization of expression array data

When dealing with large scale gene expression studies, observations are commonly contaminated by sources of unwanted variation such as platforms or batches. Not taking this unwanted variation into account when analyzing the data can lead to spurious associations and to missing important signals. When the analysis is unsupervised, e.g. when the goal is to cluster the samples or to build a correc...