Rank products: a simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments

By Rainer Breitling, P. Armengaud, Anna Amtmann, P. Herzyk. FEBS Letters, 2004

1,593 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/0498ecdf8a2723f7d36459149616336be378b0cd

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Citations in the corpus

A review of connectivity map and computational approaches in pharmacogenomics (2017, methodology): “Formally, for each disease signature, CMapBatch obtains a list of connectivity scores corresponding to all the small molecules (1309 in CMap Build 2) and combines them by using the Rank Product method [38] to assign a consensus ranking on each drug for all the tested gene signatures.”
The Arabidopsis NFYA5 Transcription Factor Is Regulated Transcriptionally and Posttranscriptionally to Promote Drought Resistance[W] (2008, methodology): “by Breitling et al. (2004). Two biological replicates were used for each genotype.”
Single-Cell Transcriptome Atlas of Murine Endothelial Cells. (2020, methodology): “Cell 180, 764–779, February 20, 2020 765 A B C D he ar t (legend on next page) 766 Cell 180, 764–779, February 20, 2020 We then used a rank product-based method to identify enriched ECmarker genes for each tissue (Breitling et al., 2004) (Table S2).”
A review of feature selection techniques in bioinformatics (2007, methodology): “Many model-free metrics, frequently borrowed from the statistics field, have demonstrated their usefulness in many gene expression studies, including the Wilcoxon rank-sum test [117], the between-within classes sum of squares (BSS/WSS) [29] and the rank products method [12].”
Characterization of the CLEAR network reveals an integrated control of cellular clearance pathways. (2011, background): “The genes that rank high in multiple lists are more likely to rank high in the final rank product list, even if they rank low in some of the lists (23).”
Chemotherapy Resistant Human Acute Myeloid Leukemia Cells are Not Enriched for Leukemic Stem Cells but Require Oxidative Metabolism (2017, neutral): “Finally, the Rank Product algorithm (5) was used to identify gene affected by AraC.”
Double-check: validation of diagnostic statistics for PLS-DA models in metabolomics studies (2011, background): “It is then clear that the larger the prediction error, the larger the PRESSD which in turn implies a smaller value of DQ2.”