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Bioinformatics Advance Access originally published online on August 21, 2008
Bioinformatics 2008 24(21):2549-2550; doi:10.1093/bioinformatics/btn446
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© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Analyzing gene perturbation screens with nested effects models in R and bioconductor

Holger Fröhlich 1, Tim Beißbarth 1, Achim Tresch 2, Dennis Kostka 3, Juby Jacob 4, Rainer Spang 4,* and F. Markowetz 5

1German Cancer Research Center (DKFZ), INF 580, 69120 Heidelberg, Germany, 2Gene Center, Ludwigs-Maximilian-Universität München, München, Germany, 3Genome Center and Department of Statistics, University of California Davis, Davis, CA 95616, USA, 4Computational Diagnostics Group, Institute of Functional Genomics, University of Regensburg, 93053 Regensburg and 5 Lewis-Sigler Institute for Integrative Genomics and Department of Computer Science, Princeton University, Princeton NJ 08544, USA

*To whom correspondence should be addressed.


  Abstract

Summary: Nested effects models (NEMs) are a class of probabilistic models introduced to analyze the effects of gene perturbation screens visible in high-dimensional phenotypes like microarrays or cell morphology. NEMs reverse engineer upstream/downstream relations of cellular signaling cascades. NEMs take as input a set of candidate pathway genes and phenotypic profiles of perturbing these genes. NEMs return a pathway structure explaining the observed perturbation effects. Here, we describe the package nem, an open-source software to efficiently infer NEMs from data. Our software implements several search algorithms for model fitting and is applicable to a wide range of different data types and representations. The methods we present summarize the current state-of-the-art in NEMs.

Availability: Our software is written in the R language and freely avail-able via the Bioconductor project at http://www.bioconductor.org.

Contact: rainer.spang{at}klinik.uni-regensburg.de

Associate Editor: Jonathan Wren

Received on June 25, 2008; revised on August 12, 2008; accepted on August 17, 2008

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 Proc. Natl. Acad. Sci. USAHome page
B. Anchang, M. J. Sadeh, J. Jacob, A. Tresch, M. O. Vlad, P. J. Oefner, and R. Spang
Special Feature: Complex Systems: From Chemistry to Systems Biology Special Feature: Modeling the temporal interplay of molecular signaling and gene expression by using dynamic nested effects models
PNAS, April 21, 2009; 106(16): 6447 - 6452.
[Abstract] [Full Text] [PDF]


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