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Bioinformatics Advance Access originally published online on January 9, 2008
Bioinformatics 2008 24(5):696-703; doi:10.1093/bioinformatics/btn001
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© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Interpool: interpreting smart-pooling results

Nicolas Thierry-Mieg * and Gilles Bailly {dagger}

TIMC-IMAG, CNRS UMR5525, Faculte de Medecine, 38706 La Tronche Cedex, France

*To whom correspondence should be addressed.


  Abstract

Motivation: In high-throughput projects aiming to identify rare positives using a binary assay, smart-pooling constitutes an appealing strategy liable of significantly reducing the number of tests while correcting for experimental noise. In order to perform simulations for choosing an appropriate set of pools, and later to interpret the experimental results, the pool outcomes must be ‘decoded’. The intuitive aim is clearly to identify the positives that gave rise to an observation, whether real or simulated. However, this goal is not well-formalized and has been the focus of very few studies.

Results: We first provide a clear combinatorial formalization of the ‘decoding problem’. We then present interpool, an exact algorithm to solve this problem. An efficient implementation is freely available. Its usefulness is illustrated in the context of yeast-two-hybrid interactome mapping with the Shifted Transversal Design.

Availability: The implementation, licensed under the GNU GPL, can be downloaded from http://www-timc.imag.fr/Nicolas.Thierry-Mieg/

Contact: nicolas.thierry-mieg{at}imag.fr

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Alfonso Valencia

{dagger}Present address: LIG, University of Grenoble 1, BP 253, 38041 Grenoble Cedex 9, France.

Received on July 6, 2007; revised on October 17, 2007; accepted on January 1, 2008

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