Minimal marker sets to discriminate among seedlines

T. Hudson, A. Stapleton, Amy M. Curley
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Abstract

Raising seeds for biological experiments is prone to error; a careful experimenter will test in the lab to verify that plants are of the intended strain. Choosing a minimal set of tests that will discriminate between all known seedlines is an instance of Minimal Test Set, a NP-complete problem. Similar biological problems, such as minimizing the number of haplotype tag SNPs, require complex nondeterministic heuristics to solve in reasonable timeframes over modest datasets. However, selecting the minimal marker set to discriminate among seedlines is less complicated than other problems considered in the literature; we show that a simple heuristic approach works well in practice. Finding all minimal sets of tests to identify 91 Zea mays recombinant inbred lines would require months of CPU time; our heuristic gives a result less than twice the minimal possible size in under five seconds, with similar performance on Arabidopsis thaliana recombinant inbred lines.
最小的标记集来区分种系
为生物实验培育种子容易出错;细心的实验人员会在实验室里进行试验,以证实植物是否属于预期的品种。选择一个最小的测试集来区分所有已知的种子系是最小测试集的一个实例,这是一个np完全问题。类似的生物学问题,例如最小化单倍型标签snp的数量,需要复杂的非确定性启发式方法在合理的时间框架内在适度的数据集上解决。然而,与文献中考虑的其他问题相比,选择最小标记集来区分种系并不复杂;我们证明了一种简单的启发式方法在实践中效果很好。找到所有最小的测试集来识别91个玉米重组自交系将需要数月的CPU时间;我们的启发式算法在5秒内给出了小于最小可能尺寸两倍的结果,在拟南芥重组自交系上具有类似的性能。
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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