title: Statistical methods and software for the analysis of highthroughput reverse genetic assays using flow cytometry readouts.
abstract: Highthroughput cell-based assays with flow cytometric readout provide a powerful technique for identifying components of biologic pathways and their interactors. Interpretation of these large datasets requires effective computational methods. We present a new approach that includes data pre-processing, visualization, quality assessment, and statistical inference. The software is freely available in the Bioconductor package prada. The method permits analysis of large screens to detect the effects of molecular interventions in cellular systems.
authors.affiliation: Division of Molecular Genome Analysis, German Cancer Research Center, INF 580, 69120 Heidelberg, Germany. f.hahne@dkfz.de
authors.forename: Florian
authors.initials: F
authors.lastname: Hahne
authors.forename: Dorit
authors.initials: D
authors.lastname: Arlt
authors.forename: Mamatha
authors.initials: M
authors.lastname: Sauermann
authors.forename: Meher
authors.initials: M
authors.lastname: Majety
authors.forename: Annemarie
authors.initials: A
authors.lastname: Poustka
authors.forename: Stefan
authors.initials: S
authors.lastname: Wiemann
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Huber
mesh_terms: D016208:Databases, Factual; D001330:Electronic Data Processing / Q000379:methods / Q000592:standards; D020869:Gene Expression Profiling; D030342:Genetic Diseases, Inborn / Q000453:epidemiology*; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical; D016017:Odds Ratio; D012984:Software