Cargando…
Improving the power of gene set enrichment analyses
BACKGROUND: Set enrichment methods are commonly used to analyze high-dimensional molecular data and gain biological insight into molecular or clinical phenotypes. One important category of analysis methods employs an enrichment score, which is created from ranked univariate correlations between phen...
Autores principales: | Roder, Joanna, Linstid, Benjamin, Oliveira, Carlos |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6525372/ https://www.ncbi.nlm.nih.gov/pubmed/31101008 http://dx.doi.org/10.1186/s12859-019-2850-1 |
Ejemplares similares
-
A dropout-regularized classifier development approach optimized for precision medicine test discovery from omics data
por: Roder, Joanna, et al.
Publicado: (2019) -
Robust identification of molecular phenotypes using semi-supervised learning
por: Roder, Heinrich, et al.
Publicado: (2019) -
Gene Set Enrichment Analyses: lessons learned from the heart failure phenotype
por: Tragante, Vinicius, et al.
Publicado: (2017) -
Computation of significance scores of unweighted Gene Set Enrichment Analyses
por: Keller, Andreas, et al.
Publicado: (2007) -
Principal component gene set enrichment (PCGSE)
por: Frost, H. Robert, et al.
Publicado: (2015)