ArticleScientific reports2022
Innovative GenExpA software for selecting suitable reference genes for reliable normalization of gene expression in melanoma.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 0 citations in OpenAlex.
- Advances in algorithms for normalizer gene selection in qRT-PCR: implications for cancer biology and precision medicine.Frontiers in genetics · 2026Review
- Analysis of qRT-PCR Data to Identify the Most Stable Reference Gene Using gQuant.Bio-protocol · 2025Article
- RNA-seq validation: software for selection of reference and variable candidate genes for RT-qPCR.BMC genomics · 2024Article
- Evaluation of Reference Genes for Real-Time Quantitative PCR Analysis in Tissues from Bumble Bees (International journal of molecular sciences · 2022Article
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4 authors at 1 institution in 1 country.
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Abstract
The algorithms commonly used to select the best stable reference gene in RT-qPCR data analysis have their limitations. We showed that simple selection of the reference gene or pair of genes with the lowest stability value from the pool of potential reference genes-a commonly used approach-is not sufficient to accurately and reliably normalize the target gene transcript and can lead to biologically incorrect conclusions. For reliable assessment of changes in a target gene expression level, we propose our innovative GenExpA software, which works in a manner independent of the experimental model and the normalizer used. GenExpA software selects the best reference by combining the NormFinder algorithm with progressive removal of the least stable gene from the candidate genes in a given experimental model and in the set of daughter models assigned to it. The reliability of references is validated based on the consistency of the statistical analyses of normalized target gene expression levels through all models, described by the coherence score (CS). The use of the CS value imparts a new quality to qPCR analysis because it clarifies how low the stability value of reference must be in order for biologically correct conclusions to be drawn. We tested our method on qPCR data for the B4GALT genes family in melanoma, which is characterized by a high mutation rate, and in melanocytes. GenExpA is available at https://github.com/DorotaHojaLukowicz/GenExpA or https://www.sciencemarket.pl/baza-programow-open-source#oferty .
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