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Stability of gene rankings from RNAi screens

Siebourg, Juliane ; Merdes, Gunter ; Misselwitz, Benjamin ; Hardt, Wolf-Dietrich ; Beerenwinkel, Niko

In: Bioinformatics, 2012, vol. 28, no. 12, p. 1612-1618

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    Titre
    • Stability of gene rankings from RNAi screens
    Auteur
    • Siebourg, Juliane. Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland, SIB Swiss Institute of Bioinformatics, 4058 Basel, Switzerland and Institute of Microbiology, Department of Biology, ETH Zurich, Wolfgang-Pauli-Strasse 10, 8093 Zurich, Switzerland
    • Merdes, Gunter. Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland, SIB Swiss Institute of Bioinformatics, 4058 Basel, Switzerland and Institute of Microbiology, Department of Biology, ETH Zurich, Wolfgang-Pauli-Strasse 10, 8093 Zurich, Switzerland
    • Misselwitz, Benjamin. Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland, SIB Swiss Institute of Bioinformatics, 4058 Basel, Switzerland and Institute of Microbiology, Department of Biology, ETH Zurich, Wolfgang-Pauli-Strasse 10, 8093 Zurich, Switzerland
    • Hardt, Wolf-Dietrich. Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland, SIB Swiss Institute of Bioinformatics, 4058 Basel, Switzerland and Institute of Microbiology, Department of Biology, ETH Zurich, Wolfgang-Pauli-Strasse 10, 8093 Zurich, Switzerland
    • Beerenwinkel, Niko. Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland, SIB Swiss Institute of Bioinformatics, 4058 Basel, Switzerland and Institute of Microbiology, Department of Biology, ETH Zurich, Wolfgang-Pauli-Strasse 10, 8093 Zurich, Switzerland
    Type de document
    • Postprint
    Identifiant OAI-PMH
    • oai:doc.rero.ch:289652
    Summary
    Motivation: Genome-wide RNA interference (RNAi) experiments are becoming a widely used approach for identifying intracellular molecular pathways of specific functions. However, detecting all relevant genes involved in a biological process is challenging, because typically only few samples per gene knock-down are available and readouts tend to be very noisy. We investigate the reliability of top scoring hit lists obtained from RNAi screens, compare the performance of different ranking methods, and propose a new ranking method to improve the reproducibility of gene selection. Results: The performance of different ranking methods is assessed by the size of the stable sets they produce, i.e. the subsets of genes which are estimated to be re-selected with high probability in independent validation experiments. Using stability selection, we also define a new ranking method, called stability ranking, to improve the stability of any given base ranking method. Ranking methods based on mean, median, t-test and rank-sum test, and their stability-augmented counterparts are compared in simulation studies and on three microscopy image RNAi datasets. We find that the rank-sum test offers the most favorable trade-off between ranking stability and accuracy and that stability ranking improves the reproducibility of all and the accuracy of several ranking methods. Availability: Stability ranking is freely available as the R/Bioconductor package staRank at http://www.cbg.ethz.ch/software/staRank. Contact: niko.beerenwinkel@bsse.ethz.ch Supplementary information: Supplementary data are available at Bioinformatics online