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Optimization of probe coverage for high-resolution oligonucleotide aCGH.

Doron Lipson¹, Zohar Yakhini, Yonatan Aumann

¹Computer Science Department Technion, Israel. dlipson@cs.technion.ac.il

Bioinformatics (Oxford, England)

|January 24, 2007

Summary

Optimizing probe selection for high-resolution array-based comparative genomic hybridization (aCGH) is crucial. This study introduces a novel formulation and efficient algorithms to improve probe selection for high-definition array design.

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Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

High-resolution genomic alteration mapping using oligonucleotide array-based comparative genomic hybridization (aCGH) is constrained by probe availability and array space.
Optimizing probe selection is essential for designing high-resolution aCGH arrays without compromising probe quality.

Purpose of the Study:

To define and solve the probe selection optimization problem for high-resolution aCGH array design.
To develop efficient algorithms for selecting optimal probes, ensuring high resolution and quality.

Main Methods:

Formulation of the probe selection problem as a 'whenever possible in-cover' optimization problem.
Development of a fast randomized algorithm with O(n log n) time complexity.
Development of a deterministic algorithm with O(n log n) time complexity.

Main Results:

The proposed 'whenever possible in-cover' formulation accurately represents the probe selection requirements.
Both randomized and deterministic algorithms efficiently solve the optimization problem.
The method demonstrated superior performance in a typical high-definition array design scenario compared to alternative approaches.

Conclusions:

The developed optimization framework and algorithms effectively address the challenges of probe selection for high-resolution aCGH.
This approach enhances the design of high-definition arrays, improving the resolution of genomic alteration mapping.