Authors:
H Fröhlich, T Beissbarth, A Tresch, D Kostka, J Jacob, R Spang, F Markowetz
Journal name: 
Bioinformatics
Citation info: 
24(21):2549-2550
Abstract: 
UNLABELLED: 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.
DOI: 
http://doi.org/10.1093/bioinformatics/btn446
Research group: 
Markowetz Group
E-pub date: 
01 Nov 2008