Deep mutational scanning

深度突变扫描
  • 文章类型: Journal Article
    变异效应(MAVE)的多重分析已成为在单个实验中询问数千个遗传变异的强大方法。这些技术在不同学科中的灵活性和广泛采用导致了数据格式和描述的异构组合,这使得生成的数据集的下游使用变得复杂。为了解决这些问题并促进MAVE数据的可重复性和重用性,我们为MAVE数据和元数据定义了一组最低信息标准,并概述了与已建立的生物医学本体相一致的受控词汇表,以描述这些实验设计。
    Multiplexed assays of variant effect (MAVEs) have emerged as a powerful approach for interrogating thousands of genetic variants in a single experiment. The flexibility and widespread adoption of these techniques across diverse disciplines have led to a heterogeneous mix of data formats and descriptions, which complicates the downstream use of the resulting datasets. To address these issues and promote reproducibility and reuse of MAVE data, we define a set of minimum information standards for MAVE data and metadata and outline a controlled vocabulary aligned with established biomedical ontologies for describing these experimental designs.
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    文章类型: Preprint
    变异效应的多重分析(MAVE)已成为在单个实验中询问数千个遗传变异的强大方法。这些技术在不同学科中的灵活性和广泛采用导致了数据格式和描述的异构组合,这使得生成的数据集的下游使用变得复杂。为了解决这些问题并促进MAVE数据的可重复性和重用性,我们为MAVE数据和元数据定义了一组最低信息标准,并概述了与已建立的生物医学本体相一致的受控词汇表,以描述这些实验设计。
    Multiplexed Assays of Variant Effect (MAVEs) have emerged as a powerful approach for interrogating thousands of genetic variants in a single experiment. The flexibility and widespread adoption of these techniques across diverse disciplines has led to a heterogeneous mix of data formats and descriptions, which complicates the downstream use of the resulting datasets. To address these issues and promote reproducibility and reuse of MAVE data, we define a set of minimum information standards for MAVE data and metadata and outline a controlled vocabulary aligned with established biomedical ontologies for describing these experimental designs.
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