Cargando…
RankProd 2.0: a refactored bioconductor package for detecting differentially expressed features in molecular profiling datasets
MOTIVATION: The Rank Product (RP) is a statistical technique widely used to detect differentially expressed features in molecular profiling experiments such as transcriptomics, metabolomics and proteomics studies. An implementation of the RP and the closely related Rank Sum (RS) statistics has been...
Autores principales: | Del Carratore, Francesco, Jankevics, Andris, Eisinga, Rob, Heskes, Tom, Hong, Fangxin, Breitling, Rainer |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5860065/ https://www.ncbi.nlm.nih.gov/pubmed/28481966 http://dx.doi.org/10.1093/bioinformatics/btx292 |
Ejemplares similares
-
A fast algorithm for determining bounds and accurate approximate p-values of the rank product statistic for replicate experiments
por: Heskes, Tom, et al.
Publicado: (2014) -
struct: an R/Bioconductor-based framework for standardized metabolomics data analysis and beyond
por: Lloyd, Gavin Rhys, et al.
Publicado: (2020) -
RankProd Combined with Genetic Algorithm Optimized Artificial Neural Network Establishes a Diagnostic and Prognostic Prediction Model that Revealed C1QTNF3 as a Biomarker for Prostate Cancer
por: Hou, Qi, et al.
Publicado: (2018) -
Importing ArrayExpress datasets into R/Bioconductor
por: Kauffmann, Audrey, et al.
Publicado: (2009) -
ipaPy2: Integrated Probabilistic Annotation (IPA) 2.0—an improved Bayesian-based method for the annotation of LC–MS/MS untargeted metabolomics data
por: Del Carratore, Francesco, et al.
Publicado: (2023)