Evidence map›Paper›PMID 35228606›Full record

ArticleScientific reports2022

Innovative GenExpA software for selecting suitable reference genes for reliable normalization of gene expression in melanoma.

Dorota Hoja-Łukowicz, Dawid Maciążek, Piotr Kościelniak, Marcelina E Janik

Open access · goldAbstract read
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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.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact, top 100% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 0 citations in OpenAlex.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Dorota Hoja-ŁukowiczInstitute of Zoology and Biomedical Research, Jagiellonian University, Gronostajowa 9, 30-387, Krakow, Poland. dorota.hoja-lukowicz@uj.edu.pl.
Dawid MaciążekSmoluchowski Institute of Physics, Jagiellonian University, Łojasiewicza 11, 30-348, Krakow, Poland.
Piotr KościelniakInstitute of Mathematics, Jagiellonian University, Łojasiewicza 6, 30-348, Kraków, Poland.
Marcelina E JanikInstitute of Zoology and Biomedical Research, Jagiellonian University, Gronostajowa 9, 30-387, Krakow, Poland. marcelina.janik@uj.edu.pl.
Jagiellonian University · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 .

Indexed as

MelanomaSoftwareGene ExpressionGene Expression ProfilingHumansReal-Time Polymerase Chain ReactionReference StandardsReproducibility of Results

Identifiers

PMID35228606
PMCPMC8885735
OpenAlexW3198325438

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.