Nested effects models for high-dimensional phenotyping screens

Florian Markowetz, Dennis Kostka, Olga G. Troyanskaya, Rainer Spang

Research output: Contribution to journalArticle

70 Citations (Scopus)

Abstract

Motivation: In high-dimensional phenotyping screens, a large number of cellular features is observed after perturbing genes by knockouts or RNA interference. Comprehensive analysis of perturbation effects is one of the most powerful techniques for attributing functions to genes, but not much work has been done so far to adapt statistical and computational methodology to the specific needs of large-scale and high-dimensional phenotyping screens. Results: We introduce and compare probabilistic methods to efficiently infer a genetic hierarchy from the nested structure of observed perturbation effects. These hierarchies elucidate the structures of signaling pathways and regulatory networks. Our methods achieve two goals: (1) they reveal clusters of genes with highly similar phenotypic profiles, and (2) they order (clusters of) genes according to subset relationships between phenotypes. We evaluate our algorithms in the controlled setting of simulation studies and show their practical use in two experimental scenarios: (1) a data set investigating the response to microbial challenge in Drosophila melanogaster, and (2) a compendium of expression profiles of Saccharomyces cerevisiae knockout strains. We show that our methods identify biologically justified genetic hierarchies of perturbation effects.

Original languageEnglish (US)
JournalBioinformatics
Volume23
Issue number13
DOIs
StatePublished - Jul 1 2007

Fingerprint

High-dimensional
Genes
Multigene Family
Gene
Perturbation
Gene Knockout Techniques
Gene Order
RNA Interference
Drosophila melanogaster
Saccharomyces cerevisiae
Signaling Pathways
Regulatory Networks
Probabilistic Methods
Drosophilidae
Saccharomyces Cerevisiae
Set theory
RNA
Phenotype
Model
Yeast

All Science Journal Classification (ASJC) codes

  • Computational Mathematics
  • Molecular Biology
  • Biochemistry
  • Clinical Biochemistry
  • Computer Science Applications
  • Statistics and Probability
  • Computational Theory and Mathematics

Cite this

Markowetz, Florian ; Kostka, Dennis ; Troyanskaya, Olga G. ; Spang, Rainer. / Nested effects models for high-dimensional phenotyping screens. In: Bioinformatics. 2007 ; Vol. 23, No. 13.
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Nested effects models for high-dimensional phenotyping screens. / Markowetz, Florian; Kostka, Dennis; Troyanskaya, Olga G.; Spang, Rainer.

In: Bioinformatics, Vol. 23, No. 13, 01.07.2007.

Research output: Contribution to journalArticle

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