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相关概念视频

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sendigR:一个R包,利用CDISC SEND数据集的价值进行交叉研究分析.

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新的 sendigR R 包可使用标准非临床数据交换 (SEND) 数据集进行交叉研究毒理学分析. 它可以构建数据库和协调术语,用于开源毒理学数据探索.

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科学领域:

  • *药理学和毒理学 *药理学和毒理学
  • * 数据科学和生物信息学

背景情况:

  • * CDISC非临床数据交换标准 (SEND) 允许在毒理学中进行数据标准化.
  • *促进SEND数据集的交叉研究分析对于药物开发至关重要.
  • *需要开源软件解决方案才能有效利用SEND数据.

研究的目的:

  • * 开发和宣传用于SEND数据集交叉研究分析的新方法.
  • *创建一个开源的R包, sendigR,用于从SEND数据集构建关系数据库.
  • * 为了使SEND数据集中的术语协调,使用受控术语.

主要方法:

  • * 在与制药用户软件交易所 (PHUSE) 合作开发R套件"sendigR".
  • * 整合了Python包"xptcleaner"用于术语协调.
  • * 包含一个R Shiny网络应用程序,用于历史控制分析,无需编码经验.

主要成果:

  • * `sendigR` R包允许用户从SEND数据集构建一个关系数据库.
  • *用户可以查询数据库进行交叉研究分析.
  • * 术语协调是通过通过"exptcleaner"对CDISC控制的术语进行映射来实现的.
  • * 非程序员可以使用R Shiny应用程序进行历史控制分析.

结论:

  • * `sendigR`为研究人员分析毒理学数据提供了一个有价值的开源工具.
  • * 该套件使经验丰富的程序员和毒理学家能够对SEND数据进行交叉研究分析.
  • * `sendigR` 在CRAN和GitHub上免费提供,促进协作开发和可访问性.