Rapid large-scale oligonucleotide selection for microarrays

S. Rahmann
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引用次数: 57

Abstract

We present the first algorithm that selects oligonucleotide probes (e.g. 25-mers) for microarray experiments on a large scale. For example, oligos for human genes can be found within 50 hours. This becomes possible by using the longest common substring as a specificity measure for candidate oligos. We present an algorithm based on a suffix array with additional information that is efficient both in terms of memory usage and running time to rank all candidate oligos according to their specificity. We also introduce the concept of master sequences to describe the sequences from which oligos are to be selected. Constraints such as oligo length, melting temperature, and self-complementarity are incorporated in the master sequence at a preprocessing stage and thus kept separate from the main selection problem. As a result, custom oligos can now be designed for any sequenced genome, just as the technology for on-site chip synthesis is becoming increasingly mature.
微阵列快速大规模寡核苷酸选择
我们提出了第一个选择寡核苷酸探针(例如25-mers)进行大规模微阵列实验的算法。例如,人类基因的寡核苷酸可以在50小时内找到。这可以通过使用最长公共子串作为候选寡核苷酸的特异性度量来实现。我们提出了一种基于带有附加信息的后缀数组的算法,该算法在内存使用和运行时间方面都很有效,可以根据候选oligos的特殊性对它们进行排名。我们还引入了主序列的概念来描述从中选择寡核苷酸的序列。在预处理阶段将寡核苷酸长度、熔化温度和自互补性等约束条件纳入主序列,从而与主选择问题分离。因此,现在可以为任何测序基因组设计定制寡核苷酸,就像现场芯片合成技术变得越来越成熟一样。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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