Suppr超能文献

用于在基于家庭的研究中估计特定年龄风险的R软件包。

The R package for estimation of age specific risk in family-based studies.

作者信息

Kubista Nicolas, Braun Danielle, Parmigiani Giovanni

机构信息

Department of Biostatistics Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States.

Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215, United States.

出版信息

Bioinform Adv. 2025 Jul 8;5(1):vbaf154. doi: 10.1093/bioadv/vbaf154. eCollection 2025.

Abstract

MOTIVATION

Reliable tools and software for penetrance (age-specific risk among those who carry a genetic variant) estimation are critical to improving clinical decision making and risk assessment for hereditary syndromes. However, there is a lack of easily usable software for penetrance estimation in family-based studies that implements a Bayesian estimation approach.

RESULTS

We introduce , an open-source R package available on CRAN, to estimate age-specific penetrance using family-history pedigree data. The package uses a Bayesian estimation approach, allowing for the incorporation of prior knowledge through the specification of priors for the parameters of the carrier distribution. It also includes options to impute missing ages during the estimation process, addressing incomplete age information which is not uncommon in pedigree datasets. Our open-source software provides a flexible and user-friendly tool for researchers to estimate penetrance in complex family-based studies, facilitating improved genetic risk assessment in hereditary syndromes.

AVAILABILITY AND IMPLEMENTATION

The package is freely available on CRAN. Source code and documentation are available at https://github.com/nicokubi/penetrance.

摘要

动机

用于估计外显率(携带遗传变异者的特定年龄风险)的可靠工具和软件对于改善遗传性综合征的临床决策和风险评估至关重要。然而,在基于家系的研究中,缺乏易于使用的采用贝叶斯估计方法的外显率估计软件。

结果

我们引入了一个可在CRAN上获取的开源R包,用于使用家族史系谱数据估计特定年龄的外显率。该包采用贝叶斯估计方法,允许通过为携带者分布参数指定先验来纳入先验知识。它还包括在估计过程中估算缺失年龄的选项,以解决系谱数据集中常见的年龄信息不完整问题。我们的开源软件为研究人员在复杂的基于家系的研究中估计外显率提供了一个灵活且用户友好的工具,有助于改善遗传性综合征的遗传风险评估。

可用性和实现方式

该包可在CRAN上免费获取。源代码和文档可在https://github.com/nicokubi/penetrance获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3078/12270257/c2985232527d/vbaf154f1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验