Processing large data sets has become an essential part of computational genomics. Greatly increased availability of sequence data from multiple sources has fueled breakthroughs in genomics and related fields but has led to computational challenges processing large sequencing experiments. The minimizer sketch is a popular method for sequence sketching that underlies core steps in computational genomics such as read mapping, sequence assembling, k-mer counting, and more. In most applications, minimizer sketches are constructed using one of few classical approaches. More recently, efforts have been put into building minimizer sketches with desirable properties compared with the classical constructions. In this survey, we review the history of the minimizer sketch, the theories developed around the concept, and the plethora of applications taking advantage of such sketches. We aim to provide the readers a comprehensive picture of the research landscape involving minimizer sketches, in anticipation of better fusion of theory and application in the future.

中文翻译：

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在计算基因组学中创建和使用最小化草图。

处理大型数据集已成为计算基因组学的重要组成部分。来自多个来源的序列数据的可用性大大增加，推动了基因组学和相关领域的突破，但也导致了处理大型测序实验的计算挑战。最小化草图是一种流行的序列草图方法，它是计算基因组学中核心步骤的基础，例如读段映射、序列组装、k 聚体计数等。在大多数应用中，最小化草图是使用几种经典方法之一构建的。最近，人们致力于构建与经典结构相比具有理想特性的最小化草图。在本次调查中，我们回顾了最小化草图的历史、围绕该概念开发的理论以及利用此类草图的大量应用程序。我们的目标是通过最小化的草图向读者提供有关研究前景的全面了解，以期将来理论与应用更好地融合。