Visual cleaning of genotype data

J. Kennedy, Martin Graham, T. Paterson, A. Law
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引用次数: 3

Abstract

While some data cleaning tasks can be performed automatically, many more require expert human guidance to steer the cleaning process, especially if erroneous or unclean data is a product of relationships between entities. An example is pedigree genotype data: inheritance hierarchies in which the correctness of genotype data for any individual is judged on comparison to their relations' genotypes, as individuals should inherit DNA from their assumed ancestors. Thus, cleaning this data must consider the relationships between individuals; sometimes this means more data must be cleaned than first assumed, while in other situations it means errors across many individuals can be remedied by cleaning the data of a shared relation. Such judgements require a domain expert to hypothesise the effect changing particular data has on the wider data set. Using a visualization tool with the ability to undertake what-if interactions can assist a user in correctly cleaning such data. We achieve this by closely coupling an existing pedigree visualisation technique, VIPER, with a genotype cleaning algorithm, and then develop necessary extensions to the visualization to allow interactive data cleaning. A comparative user evaluation with biologists shows the advantages of this visualisation design over an existing cleaning tool and we discuss the challenges in the design of visual cleaning tools in which errors may be transitive.
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基因型数据的可视化清理
虽然有些数据清理任务可以自动执行,但更多的任务需要人工专家指导来引导清理过程,特别是当错误或不干净的数据是实体之间关系的产物时。一个例子是谱系基因型数据:在遗传层次中,任何个体的基因型数据的正确性都是通过与其亲属的基因型进行比较来判断的,因为个体应该从他们假定的祖先那里继承DNA。因此,清理这些数据必须考虑个体之间的关系;有时,这意味着必须清理的数据比最初假设的要多,而在其他情况下,这意味着可以通过清理共享关系中的数据来纠正许多个人之间的错误。这样的判断需要一个领域专家来假设改变特定数据对更广泛的数据集的影响。使用能够进行假设交互的可视化工具可以帮助用户正确地清理此类数据。我们通过将现有的系谱可视化技术VIPER与基因型清洗算法紧密耦合来实现这一目标,然后开发必要的可视化扩展以允许交互式数据清洗。与生物学家的比较用户评估显示了这种可视化设计优于现有清洁工具的优势,我们讨论了视觉清洁工具设计中的挑战,其中错误可能是可传递的。
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