Data Normalization Strategies for MicroRNA Quantification

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...

Normalization for Relative Quantification of mRNA and microRNA in Soybean Exposed to Various Abiotic Stresses

Plant microRNAs are small non-coding, endogenic RNA molecule (containing 20-24 nucleotides) produced from miRNA precursors (pri-miRNA and pre-miRNA). Evidence suggests that up and down regulation of the miRNA targets the mRNA genes involved in resistance against biotic and abiotic stresses. Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is a powerful technique ...

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...