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aFold – using polynomial uncertainty modelling for differential gene expression estimation from RNA sequencing data
BACKGROUND: Data normalization and identification of significant differential expression represent crucial steps in RNA-Seq analysis. Many available tools rely on assumptions that are often not met by real data, including the common assumption of symmetrical distribution of up- and down-regulated ge...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2019
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6509820/ https://www.ncbi.nlm.nih.gov/pubmed/31077153 http://dx.doi.org/10.1186/s12864-019-5686-1 |