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生物医学研究中的分析代码共享实践.

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  • 1Titus Family Department of Clinical Pharmacy, University of Southern California, Los Angeles, California, United States.

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此摘要是机器生成的。

大多数生物医学研究未能共享分析代码,阻碍了可复制性. 加强代码共享实践对于科学透明度和加速发现至关重要.

关键词:
可访问性 可访问性代码共享 代码共享 代码共享数据共享数据的共享.开放式访问 - 开放式访问这是一个开源的开源软件.可复制性 可复制性透明度 透明度 透明度

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科学领域:

  • 生物医学研究的研究.
  • 计算生物学是一种计算生物学.
  • 数据科学是数据科学.

背景情况:

  • 数据驱动的计算分析在现代生物医学研究中至关重要.
  • 缺乏共享的研究成果 (数据,代码,方法) 阻碍了研究的透明度和可重复性.
  • 由于文件,代码和数据的共享不足,许多已发表的研究是不可重复的.

研究的目的:

  • 分析生物医学研究出版物中代码共享的程度.
  • 识别与代码可用性和可重复性相关的因素.
  • 提出改善代码共享实践的策略.

主要方法:

  • 综合分析了2016-2021年间发表的453份生物医学手稿.
  • 评估代码可用性,数据共享和代码组织.
  • 统计分析以确定代码可用性声明,分析类型和代码共享之间的关联.

主要成果:

  • 在分析的手稿中,50.1%未能分享分析代码.
  • 大多数共享代码的研究没有共享数据等额外的研究成果.
  • 只有10%的文章以结构化,可重复的方式组织代码.
  • 代码可用性声明与代码可用性增加有显著的关联.
  • 进行二次分析的研究比主要分析更有可能共享代码.

结论:

  • 在生物医学研究中,代码共享实践存在重大缺陷,影响了可重现性.
  • 促进代码可用性声明和结构化的代码组织是必不可少的.
  • 优先考虑开放科学实践,包括代码和数据共享,是提高科学严谨性,协作和加速发现的必要条件.