Engineering a scalable placement heuristic for DNA probe arrays

  • Authors:
  • A. B. Kahng;I. Mandoiu;P. Pevzner;S. Reda;A. Zelikovsky

  • Affiliations:
  • University of California at San Diego, La Jolla, CA;University of California at San Diego, La Jolla, CA;University of California at San Diego, La Jolla, CA;University of California at San Diego, La Jolla, CA;Georgia State University, Atlanta, GA

  • Venue:
  • RECOMB '03 Proceedings of the seventh annual international conference on Research in computational molecular biology
  • Year:
  • 2003

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Abstract

Design of DNA arrays for very large-scale immobilized polymer synthesis (VLSIPS) [8] seeks to minimize effects of unintended illumination during mask exposure steps. [9, 14] formulate this requirement as the Border Minimization Problem and give methods for placement (at array sites) and embedding (in the mask sequence) of probes in both synchronous and asynchronous regimes. These previous methods do not address several practical details of the application and, more critically, are not scalable to the O(108) probes contemplated for next-generation probe arrays. In this work, we make two main contributions:We give improved dynamic programming algorithms that perform probe embedding to minimize the number border conflicts while accounting for distance- and position-dependent border conflict weights, as well as the presence of polymorphic probes in the instance. We describe and experimentally validate the "engineering" of a scalable, high-quality asynchronous placement heuristic (which is moreover easily parallelizable) for DNA array design. Our heuristic is enabled by a novel approach for simultaneous re-placement and optimal re-embedding of an "independent set" of probes within a small window of the array..