PopMLvis: a tool for analysis and visualization of population structure using genotype data from genome-wide association studies

IF 2.9 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Mohamed Elshrif, Keivin Isufaj, Khalid Kunji, Mohamad Saad
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引用次数: 0

Abstract

One of the aims of population genetics is to identify genetic differences/similarities among individuals of multiple ancestries. Many approaches including principal component analysis, clustering, and maximum likelihood techniques can be used to assign individuals to a given ancestry based on their genetic makeup. Although there are several tools that implement such algorithms, there is a lack of interactive visual platforms to run a variety of algorithms in one place. Therefore, we developed PopMLvis, a platform that offers an interactive environment to visualize genetic similarity data using several algorithms, and generate figures that can be easily integrated into scientific articles.
PopMLvis:利用全基因组关联研究的基因型数据进行群体结构分析和可视化的工具
群体遗传学的目标之一是确定多个祖先个体之间的遗传差异/相似性。包括主成分分析、聚类和最大似然技术在内的许多方法都可用于根据个体的基因构成将其归入特定祖先。虽然有多种工具可以实现这些算法,但目前还缺乏可在一个地方运行多种算法的交互式可视化平台。因此,我们开发了 PopMLvis,这是一个提供交互式环境的平台,可使用多种算法可视化遗传相似性数据,并生成可轻松整合到科学文章中的图表。
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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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