Biomedical data are usually analyzed at the univariate level, focused on a single primary outcome measure to provide insight into systems biology, complex disease states, and precision medicine opportunities. More broadly, these complex biological and disease states can be detected as common factors emerging from the relationships among measured variables using multivariate approaches. 'Syndromics' refers to an analytical framework for measuring disease states using principal component analysis and related multivariate statistics as primary tools for extracting underlying disease patterns. A key part of the syndromic workflow is the interpretation, the visualization, and the study of robustness of the main components that characterize the disease space. We present a new software package, syndRomics, an open-source R package with utility for component visualization, interpretation, and stability for syndromic analysis. We document the implementation of syndRomics and illustrate the use of the package in case studies of neurological trauma data.

中文翻译：

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使用新型 R 包 syndRomics 通过主成分对疾病空间进行可重复分析

生物医学数据通常在单变量水平上进行分析，专注于单一的主要结果测量，以提供对系统生物学、复杂疾病状态和精准医学机会的洞察。更广泛地说，这些复杂的生物和疾病状态可以被检测为使用多元方法从测量变量之间的关系中出现的共同因素。“综合征”是指使用主成分分析和相关的多变量统计作为提取潜在疾病模式的主要工具来测量疾病状态的分析框架。综合征工作流程的一个关键部分是解释、可视化和研究表征疾病空间的主要成分的稳健性。我们提出了一个新的软件包 syndRomics，一个开源 R 包，具有​​用于组件可视化、解释和稳定性分析的实用程序。我们记录了 syndRomics 的实施，并说明了该软件包在神经创伤数据案例研究中的使用。