RankProd: Rank Product method for identifying differentially expressed genes with application in meta-analysis. Non-parametric method for identifying differentially expressed (up- or down- regulated) genes based on the estimated percentage of false predictions (pfp). The method can combine data sets from different origins (meta-analysis) to increase the power of the identification.

References in zbMATH (referenced in 6 articles )

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  1. Mathé, Ewy (ed.); Davis, Sean (ed.): Statistical genomics. Methods and protocols (2016)
  2. Cope, Leslie; Naiman, Daniel Q.; Parmigiani, Giovanni: Integrative correlation: properties and relation to canonical correlations (2014)
  3. Li, Jia; Tseng, George C.: An adaptively weighted statistic for detecting differential gene expression when combining multiple transcriptomic studies (2011)
  4. Ma, Shuangge; Huang, Jian: Regularized gene selection in cancer microarray meta-analysis (2009) ioport
  5. Zintzaras, Elias; Ioannidis, John P. A.: Meta-analysis for ranked discovery datasets: theoretical framework and empirical demonstration for microarrays (2008)
  6. Hong, Fangxin; Breitling, Rainer; Mcentee, Connor W.; Wittner, Ben S.; Nemhauser, Jennifer L.; Chory, Joanne: Rankprod: A bioconductor package for detecting differentially expressed genes in meta-analysis (2006) ioport