Literature DB >> 20951135

The rank product method with two samples.

James A Koziol1.   

Abstract

Breitling et al. (2004) introduced a statistical technique, the rank product method, for detecting differentially regulated genes in replicated microarray experiments. The technique has achieved widespread acceptance and is now used more broadly, in such diverse fields as RNAi analysis, proteomics, and machine learning. In this note, we extend the rank product method to the two sample setting, provide distribution theory attending the rank product method in this setting, and give numerical details for implementing the method.
Copyright © 2010 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

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Year:  2010        PMID: 20951135      PMCID: PMC2975561          DOI: 10.1016/j.febslet.2010.10.012

Source DB:  PubMed          Journal:  FEBS Lett        ISSN: 0014-5793            Impact factor:   4.124


  10 in total

1.  Rank-based methods as a non-parametric alternative of the T-statistic for the analysis of biological microarray data.

Authors:  Rainer Breitling; Pawel Herzyk
Journal:  J Bioinform Comput Biol       Date:  2005-10       Impact factor: 1.122

2.  RankProd: a bioconductor package for detecting differentially expressed genes in meta-analysis.

Authors:  Fangxin Hong; Rainer Breitling; Connor W McEntee; Ben S Wittner; Jennifer L Nemhauser; Joanne Chory
Journal:  Bioinformatics       Date:  2006-09-18       Impact factor: 6.937

3.  A classification model for the Leiden proteomics competition.

Authors:  Huub C J Hoefsloot; Suzanne Smit; Age K Smilde
Journal:  Stat Appl Genet Mol Biol       Date:  2008-02-19

4.  A comparison of meta-analysis methods for detecting differentially expressed genes in microarray experiments.

Authors:  Fangxin Hong; Rainer Breitling
Journal:  Bioinformatics       Date:  2008-01-18       Impact factor: 6.937

5.  The wisdom of the commons: ensemble tree classifiers for prostate cancer prognosis.

Authors:  James A Koziol; Anne C Feng; Zhenyu Jia; Yipeng Wang; Seven Goodison; Michael McClelland; Dan Mercola
Journal:  Bioinformatics       Date:  2008-07-15       Impact factor: 6.937

6.  Comments on the rank product method for analyzing replicated experiments.

Authors:  James A Koziol
Journal:  FEBS Lett       Date:  2010-01-20       Impact factor: 4.124

Review 7.  Statistical methods for analysis of high-throughput RNA interference screens.

Authors:  Amanda Birmingham; Laura M Selfors; Thorsten Forster; David Wrobel; Caleb J Kennedy; Emma Shanks; Javier Santoyo-Lopez; Dara J Dunican; Aideen Long; Dermot Kelleher; Queta Smith; Roderick L Beijersbergen; Peter Ghazal; Caroline E Shamu
Journal:  Nat Methods       Date:  2009-08       Impact factor: 28.547

8.  The yeast vacuolar membrane proteome.

Authors:  Elena Wiederhold; Tejas Gandhi; Hjalmar P Permentier; Rainer Breitling; Bert Poolman; Dirk J Slotboom
Journal:  Mol Cell Proteomics       Date:  2008-11-10       Impact factor: 5.911

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

Authors:  Rainer Breitling; Patrick Armengaud; Anna Amtmann; Pawel Herzyk
Journal:  FEBS Lett       Date:  2004-08-27       Impact factor: 4.124

10.  Comparison and evaluation of methods for generating differentially expressed gene lists from microarray data.

Authors:  Ian B Jeffery; Desmond G Higgins; Aedín C Culhane
Journal:  BMC Bioinformatics       Date:  2006-07-26       Impact factor: 3.169

  10 in total
  5 in total

1.  The Cohesin Release Factor WAPL Restricts Chromatin Loop Extension.

Authors:  Judith H I Haarhuis; Robin H van der Weide; Vincent A Blomen; J Omar Yáñez-Cuna; Mario Amendola; Marjon S van Ruiten; Peter H L Krijger; Hans Teunissen; René H Medema; Bas van Steensel; Thijn R Brummelkamp; Elzo de Wit; Benjamin D Rowland
Journal:  Cell       Date:  2017-05-04       Impact factor: 41.582

2.  RankProd 2.0: a refactored bioconductor package for detecting differentially expressed features in molecular profiling datasets.

Authors:  Francesco Del Carratore; Andris Jankevics; Rob Eisinga; Tom Heskes; Fangxin Hong; Rainer Breitling
Journal:  Bioinformatics       Date:  2017-09-01       Impact factor: 6.937

3.  Novel analytical methods to interpret large sequencing data from small sample sizes.

Authors:  Florence Lichou; Sébastien Orazio; Stéphanie Dulucq; Gabriel Etienne; Michel Longy; Christophe Hubert; Alexis Groppi; Alain Monnereau; François-Xavier Mahon; Béatrice Turcq
Journal:  Hum Genomics       Date:  2019-08-30       Impact factor: 4.639

4.  A Simple Rank Product Approach for Analyzing Two Classes.

Authors:  Tae Young Yang
Journal:  Bioinform Biol Insights       Date:  2015-07-16

5.  Induction of PrMADS10 on the lower side of bent pine tree stems: potential role in modifying plant cell wall properties and wood anatomy.

Authors:  Nicolás Cruz; Tamara Méndez; Patricio Ramos; Daniela Urbina; Andrea Vega; Rodrigo A Gutiérrez; María A Moya-León; Raúl Herrera
Journal:  Sci Rep       Date:  2019-12-12       Impact factor: 4.379

  5 in total

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