GeneRiskCalc:一个基于网络的工具,用于病例对照研究中的遗传风险关联分析。

IF 3.3 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Amrit Sudershan, Kuljeet Singh, Parvinder Kumar
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引用次数: 0

摘要

背景:遗传关联研究在识别疾病相关变异方面发挥着关键作用,但由于依赖于手工方法或多种软件工具,研究人员在执行Hardy-Weinberg平衡检验、优势比和置信区间等基本计算方面面临挑战。我们的目标是开发GeneRiskCalc,这是一个集成的基于网络的平台,通过自动化Hardy-Weinberg平衡评估、置信区间计算的优势比和病例对照研究中的可视化数据呈现来简化遗传关联分析。使用HTML/CSS/JavaScript框架,我们开发了具有三个核心功能的在线软件:(1)自动化HWE评估;(2)统计验证的95%置信区间的比值比计算;(3)用于数据可视化的动态森林图生成。该工具设计了一个直观的界面,以尽量减少必要的统计专业知识。结果:该工具名为遗传风险关联计算器(GeneRiskCalc),在HWE检测(χ2验证)和关联指标(优势比和置信区间)中显示出较高的计算准确性。结果与已建立的统计方法交叉验证,证实了其可靠性。此外,集成的森林绘图仪可以立即可视化多个遗传模型的效应大小,促进对遗传关联的全面解释。结论:通过将基本分析步骤集成到单一平台中,GeneRiskCalc简化了遗传流行病学工作流程,解决了数据分析中的关键挑战。其用户友好的界面增强了可访问性,促进了可重复性,并加速了遗传关联研究的研究。该工具可在GeneRiskCalc (https://sites.google.com/view/GeneRiskCalc/home?authuser=0)免费获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

GeneRiskCalc: a web-based tool for genetic risk association analysis in case-control studies.

GeneRiskCalc: a web-based tool for genetic risk association analysis in case-control studies.

GeneRiskCalc: a web-based tool for genetic risk association analysis in case-control studies.

GeneRiskCalc: a web-based tool for genetic risk association analysis in case-control studies.

Background: Genetic association studies play a pivotal role in identifying disease-associated variants, but researchers face challenges in performing essential calculations like Hardy-Weinberg equilibrium testing, odds ratios, and confidence intervals due to reliance on manual methods or multiple software tools. We aimed to develop GeneRiskCalc, an integrated web-based platform that simplifies genetic association analysis by automating Hardy-Weinberg equilibrium assessment, odds ratios with confidence interval calculation, and visual data presentation in case-control studies. Using an HTML/CSS/JavaScript framework, we developed online software with three core functionalities: (1) automated HWE evaluation, (2) odds ratio with 95% confidence interval computation with statistical validation, and (3) dynamic Forest Plot generation for data visualization. The tool was designed with an intuitive interface to minimize prerequisite statistical expertise.

Results: The tool, named the Genetic Risk Association Calculator (GeneRiskCalc), demonstrated high computational accuracy in HWE testing (χ2 validation) and association metrics (odds ratio and confidence interval). The results were cross-validated against established statistical methods, confirming their reliability. Furthermore, the integrated Forest Plotter enabled immediate visualization of effect sizes across multiple genetic models, facilitating a comprehensive interpretation of genetic associations.

Conclusion: By integrating essential analytical steps into a single platform, the GeneRiskCalc, streamlines genetic epidemiology workflows, addressing key challenges in data analysis. Its user-friendly interface enhances accessibility, promotes reproducibility, and accelerates research in genetic association studies. The tool is freely available at GeneRiskCalc ( https://sites.google.com/view/GeneRiskCalc/home?authuser=0 ).

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来源期刊
BMC Bioinformatics
BMC Bioinformatics 生物-生化研究方法
CiteScore
5.70
自引率
3.30%
发文量
506
审稿时长
4.3 months
期刊介绍: BMC Bioinformatics is an open access, peer-reviewed journal that considers articles on all aspects of the development, testing and novel application of computational and statistical methods for the modeling and analysis of all kinds of biological data, as well as other areas of computational biology. BMC Bioinformatics is part of the BMC series which publishes subject-specific journals focused on the needs of individual research communities across all areas of biology and medicine. We offer an efficient, fair and friendly peer review service, and are committed to publishing all sound science, provided that there is some advance in knowledge presented by the work.
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