RefFinder: a web-based tool for comprehensively analyzing and identifying reference genes.
Funct Integr Genomics
; 23(2): 125, 2023 Apr 15.
Article
em En
| MEDLINE
| ID: mdl-37060478
ABSTRACT
Although many genes may serve as reference genes, they may cause different expression patterns by selecting different reference genes because no single gene is expressed consistently in all tested tissues of an organism under all environmental and developmental conditions. Thus, it is becoming increasingly important and necessary to identify suitable reference genes before performing gene expression analysis. Currently, there are several computational tools available for evaluating the stability of candidate reference genes. These tools are based on different statistical algorithms and may produce different rankings in stability within the same reference gene study. To date, the RefFinder is the only web-based tool available for comparing and evaluating housekeeping genes as candidates to be reference genes. In this tool, we integrated the four currently available computational programs (geNorm, NormFinder, BestKeeper, and the comparative ΔCt method) into a web-based tool for evaluating the stability and reliability of reference genes. According to the gene stability rankings derived from the four programs, we assigned an appropriate weight to each gene and calculated the geometric mean of weights for the final rankings. Aside from the overall ranking, a single program or combination of the four programs can be selected for evaluating the ranking of candidate reference genes. This tool has been widely used and validated by many research laboratories around the world. You may use this tool at http//www.heartcure.com.au/reffinder/ or https//blooge.cn/RefFinder/ . You can also download this algorithm program from https//github.com/fulxie/RefFinder and setup on your own computer. RefFinder is developed by PHP. Users can deploy it to a Php-based server (Apache + PHP) and run it.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Perfilação da Expressão Gênica
Tipo de estudo:
Prognostic_studies
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article