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Biological screens from linear codes: theory and tools

Yaniv Erlich, Anna Gilbert, Hung Ngo, Atri Rudra, Nicolas Thierry-Mieg, Mary Wootters, Dina Zielinski, Or Zuk
doi: https://doi.org/10.1101/035352
Yaniv Erlich
*Department of Computer Science, Fu Foundation School of Engineering, Columbia University, New York, NY, 10027, USA, Center for Computational Biology and Bioinformatics, Columbia University, New York, NY, 10027, USA, and New York Genome Center, New York, 10013, USA
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Anna Gilbert
†Department of Mathematics, University of Michigan, 530 S. Church Street, Ann Arbor, MI 48109
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Hung Ngo
‡Department of Computer Science and Engineering, University at Buffalo, Buffalo, NY 14260
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Atri Rudra
‡Department of Computer Science and Engineering, University at Buffalo, Buffalo, NY 14260
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Nicolas Thierry-Mieg
§TIMC-IMAG/BCM, UMR 5525 CNRS / UJF-Grenoble 1, Grenoble, F-38041, FRANCE
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Mary Wootters
¶Carnegie Mellon University, School of Computer Science, 5000 Forbes Avenue, Pittsburgh, PA 15213
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Dina Zielinski
*Department of Computer Science, Fu Foundation School of Engineering, Columbia University, New York, NY, 10027, USA, Center for Computational Biology and Bioinformatics, Columbia University, New York, NY, 10027, USA, and New York Genome Center, New York, 10013, USA
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Or Zuk
‖Department of Statistics, The Hebrew University, Mt. Scopus, Jerusalem, 91905, ISRAEL
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Abstract

Molecular biology increasingly relies on large screens where enormous numbers of specimens are systematically assayed in the search for a particular, rare outcome. These screens include the systematic testing of small molecules for potential drugs and testing the association between genetic variation and a phenotype of interest. While these screens are “hypothesis-free,” they can be wasteful; pooling the specimens and then testing the pools is more efficient. We articulate in precise mathematical ways the type of structures useful in combinatorial pooling designs so as to eliminate waste, to provide light weight, flexible, and modular designs. We show that Reed-Solomon codes, and more generally linear codes, satisfy all of these mathematical properties. We further demonstrate the power of this technique with Reed-Solomonbased biological experiments. We provide general purpose tools for experimentalists to construct and carry out practical pooling designs with rigorous guarantees for large screens.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted December 25, 2015.
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Biological screens from linear codes: theory and tools
Yaniv Erlich, Anna Gilbert, Hung Ngo, Atri Rudra, Nicolas Thierry-Mieg, Mary Wootters, Dina Zielinski, Or Zuk
bioRxiv 035352; doi: https://doi.org/10.1101/035352
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Biological screens from linear codes: theory and tools
Yaniv Erlich, Anna Gilbert, Hung Ngo, Atri Rudra, Nicolas Thierry-Mieg, Mary Wootters, Dina Zielinski, Or Zuk
bioRxiv 035352; doi: https://doi.org/10.1101/035352

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