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Journal of Computational Biology
Handling Long Targets and Errors in Sequencing by Hybridization

To cite this article:
Eran Halperin, Shay Halperin, Tzvika Hartman, Ron Shamir. Journal of Computational Biology. June 2003, 10(3-4): 483-497. doi:10.1089/10665270360688138.

Published in Volume: 10 Issue 3-4: July 5, 2004

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Eran Halperin
CS Division, Soda Hall, University of California Berkeley, CA 94720-1776
Shay Halperin
School of Computer Science, Tel-Aviv University, Tel-Aviv 69978, Israel
Tzvika Hartman
Department of Applied Mathematics and Computer Science, Weizmann Institute, Rehovot 76100, Israel
Ron Shamir
School of Computer Science, Tel-Aviv University, Tel-Aviv 69978, Israel

Sequencing by hybridization (SBH) is a DNA sequencing technique, in which the sequence is reconstructed using its k-mer content. This content, which is called the spectrum of the sequence, is obtained by hybridization to a universal DNA array. Standard universal arrays contain all k-mers for some fixed k, typically 8 to 10. Currently, in spite of its promise and elegance, SBH is not competitive with standard gel-based sequencing methods. This is due to two main reasons: lack of tools to handle realistic levels of hybridization errors and an inherent limitation on the length of uniquely reconstructible sequence by standard universal arrays. In this paper, we deal with both problems. We introduce a simple polynomial reconstruction algorithm which can be applied to spectra from standard arrays and has provable performance in the presence of both false negative and false positive errors. We also propose a novel design of chips containing universal bases that differs from the one proposed by Preparata et al. (1999). We give a simple algorithm that uses spectra from such chips to reconstruct with high probability random sequences of length lower only by a squared log factor compared to the information theoretic bound. Our algorithm is very robust to errors and has a provable performance even if there are both false negative and false positive errors. Simulations indicate that its sensitivity to errors is also very small in practice.

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