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WISARD: workbench for integrated superfast association studies for related datasets

机译：WISARD：用于相关数据集的集成超快速关联研究的工作台

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A Mendelian transmission produces phenotypic and genetic relatedness between family members, giving family-based analytical methods an important role in genetic epidemiological studies—from heritability estimations to genetic association analyses. With the advance in genotyping technologies, whole-genome sequence data can be utilized for genetic epidemiological studies, and family-based samples may become more useful for detecting de novo mutations. However, genetic analyses employing family-based samples usually suffer from the complexity of the computational/statistical algorithms, and certain types of family designs, such as incorporating data from extended families, have rarely been used. We present a Workbench for Integrated Superfast Association studies for Related Data (WISARD) programmed in C/C++. WISARD enables the fast and a comprehensive analysis of SNP-chip and next-generation sequencing data on extended families, with applications from designing genetic studies to summarizing analysis results. In addition, WISARD can automatically be run in a fully multithreaded manner, and the integration of R software for visualization makes it more accessible to non-experts. Comparison with existing toolsets showed that WISARD is computationally suitable for integrated analysis of related subjects, and demonstrated that WISARD outperforms existing toolsets. WISARD has also been successfully utilized to analyze the large-scale massive sequencing dataset of chronic obstructive pulmonary disease data (COPD), and we identified multiple genes associated with COPD, which demonstrates its practical value.
机译：孟德尔传播在家庭成员之间产生表型和遗传相关性，从而使基于家庭的分析方法在遗传流行病学研究中（从遗传力估计到遗传关联分析）具有重要作用。随着基因分型技术的进步，全基因组序列数据可用于遗传流行病学研究，基于家庭的样本可能对于检测从头突变更为有用。但是，采用基于家庭的样本进行的遗传分析通常会遭受计算/统计算法的复杂性，并且很少使用某些类型的家庭设计，例如合并来自大家庭的数据。我们提供了一个使用C / C ++编程的相关数据综合超快速关联研究（WISARD）的工作台。 WISARD可以对大范围的SNP芯片和下一代测序数据进行快速而全面的分析，其用途包括设计基因研究到总结分析结果。此外，WISARD可以自动以完全多线程的方式运行，并且R软件的可视化集成使其更易于非专家使用。与现有工具集的比较表明，WISARD在计算上适合于相关主题的综合分析，并证明WISARD的性能优于现有工具集。 WISARD还已成功地用于分析慢性阻塞性肺疾病数据（COPD）的大规模大规模测序数据集，并且我们鉴定了与COPD相关的多个基因，证明了其实用价值。

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