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Statistical methods and software for the analysis of highthroughput reverse genetic assays using flow cytometry readouts

Florian Hahne1*, Dorit Arlt1, Mamatha Sauermann1, Meher Majety1, Annemarie Poustka1, Stefan Wiemann1 and Wolfgang Huber2

Author Affiliations

1 Division of Molecular Genome Analysis, German Cancer Research Center, INF 580, 69120 Heidelberg, Germany

2 EMBL - European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge CB10 1SD, UK

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Genome Biology 2006, 7:R77  doi:10.1186/gb-2006-7-8-r77

Published: 17 August 2006


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.