Thessen Anne E, Marvel Skylar, Achenbach J C, Fischer Stephan, Haendel Melissa A, Hayward Kimberly, Klüver Nils, Könemann Sarah, Legradi Jessica, Lein Pamela, Leong Connor, Mylroie J Erik, Padilla Stephanie, Perone Dante, Planchart Antonio, Prieto Rafael Miñana, Muriana Arantza, Quevedo Celia, Reif David, Ryan Kristen, Stinckens Evelyn, Truong Lisa, Vergauwen Lucia, Vom Berg Colette, Wilbanks Mitch, Yaghoobi Bianca, Hamm Jon
Center for Health AI, University of Colorado Anschutz Medical Campus, Aurora, CO, United States.
Department of Biological Sciences, Bioinformatics Research Center, North Carolina State University, Raleigh, NC, United States.
Front Toxicol. 2022 Mar 11;4:817999. doi: 10.3389/ftox.2022.817999. eCollection 2022.
Toxicological evaluation of chemicals using early-life stage zebrafish () involves the observation and recording of altered phenotypes. Substantial variability has been observed among researchers in phenotypes reported from similar studies, as well as a lack of consistent data annotation, indicating a need for both terminological and data harmonization. When examined from a data science perspective, many of these apparent differences can be parsed into the same or similar endpoints whose measurements differ only in time, methodology, or nomenclature. Ontological knowledge structures can be leveraged to integrate diverse data sets across terminologies, scales, and modalities. Building on this premise, the National Toxicology Program's Systematic Evaluation of the Application of Zebrafish in Toxicology undertook a collaborative exercise to evaluate how the application of standardized phenotype terminology improved data consistency. To accomplish this, zebrafish researchers were asked to assess images of zebrafish larvae for morphological malformations in two surveys. In the first survey, researchers were asked to annotate observed malformations using their own terminology. In the second survey, researchers were asked to annotate the images from a list of terms and definitions from the Zebrafish Phenotype Ontology. Analysis of the results suggested that the use of ontology terms increased consistency and decreased ambiguity, but a larger study is needed to confirm. We conclude that utilizing a common data standard will not only reduce the heterogeneity of reported terms but increases agreement and repeatability between different laboratories. Thus, we advocate for the development of a zebrafish phenotype atlas to help laboratories create interoperable, computable data.
利用斑马鱼幼体进行化学品的毒理学评估涉及对改变的表型进行观察和记录。研究人员在类似研究报告的表型中观察到了很大的变异性，同时也缺乏一致的数据注释，这表明需要在术语和数据方面进行协调统一。从数据科学的角度审视时，许多这些明显的差异可以解析为相同或相似的终点指标，其测量仅在时间、方法或命名上有所不同。本体知识结构可用于整合跨术语、尺度和模式的不同数据集。在此前提下，国家毒理学计划的斑马鱼在毒理学中应用的系统评估开展了一项合作活动，以评估标准化表型术语的应用如何提高数据一致性。为实现这一目标，斑马鱼研究人员被要求在两项调查中评估斑马鱼幼体的形态畸形图像。在第一次调查中，研究人员被要求使用他们自己的术语注释观察到的畸形。在第二次调查中，研究人员被要求根据斑马鱼表型本体的术语和定义列表注释图像。结果分析表明，使用本体术语提高了一致性并减少了歧义，但需要更大规模的研究来证实。我们得出结论，采用通用数据标准不仅会减少报告术语的异质性，还会提高不同实验室之间的一致性和可重复性。因此，我们主张开发一个斑马鱼表型图谱，以帮助实验室创建可互操作、可计算的数据。
