MP-LASSO图:用于可视化基因组数据组LASSO分析的多级极坐标图。

Q2 Agricultural and Biological Sciences Genomics and Informatics Pub Date : 2022-12-01 DOI:10.5808/gi.22075
Min Song, Minhyuk Lee, Taesung Park, Mira Park
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引用次数: 0

摘要

惩罚回归已广泛应用于全基因组关联研究中,用于联合分析以发现遗传关联。在惩罚回归模型中,最小绝对收缩和选择算子(Lasso)方法通过将模型中的一些系数缩小到零,有效地从模型中去除一些系数。为了处理群体结构,如基因和途径,提出了几种改进的Lasso惩罚,包括群Lasso和稀疏群Lasso。Group Lasso确保了预定义组级别的稀疏性,消除了不重要的组。稀疏组Lasso像组Lasso一样执行组选择,但也像Lasso一样执行个体选择。虽然这些稀疏方法在高维遗传研究中很有用,但用许多组和系数来解释结果并不简单。拉索的结果通常表示为回归系数的轨迹图。然而,很少有研究对群体信息的系统化可视化进行探索。在本研究中,我们提出了一个多级极坐标Lasso (MP-Lasso)图,它可以有效地表示群Lasso和稀疏群Lasso分析的结果。开发了一个绘制mp -套索图的Rpackage。通过一个真实的遗传数据应用,我们证明了我们的MP-Lasso图表包有效地可视化Lasso, Lasso组和稀疏组Lasso的结果。
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MP-LASSO chart: a multi-level polar chart for visualizing group LASSO analysis of genomic data.

Penalized regression has been widely used in genome-wide association studies for jointanalyses to find genetic associations. Among penalized regression models, the least absolute shrinkage and selection operator (Lasso) method effectively removes some coefficientsfrom the model by shrinking them to zero. To handle group structures, such as genes andpathways, several modified Lasso penalties have been proposed, including group Lasso andsparse group Lasso. Group Lasso ensures sparsity at the level of pre-defined groups, eliminating unimportant groups. Sparse group Lasso performs group selection as in group Lasso,but also performs individual selection as in Lasso. While these sparse methods are useful inhigh-dimensional genetic studies, interpreting the results with many groups and coefficients is not straightforward. Lasso's results are often expressed as trace plots of regressioncoefficients. However, few studies have explored the systematic visualization of group information. In this study, we propose a multi-level polar Lasso (MP-Lasso) chart, which caneffectively represent the results from group Lasso and sparse group Lasso analyses. An Rpackage to draw MP-Lasso charts was developed. Through a real-world genetic data application, we demonstrated that our MP-Lasso chart package effectively visualizes the resultsof Lasso, group Lasso, and sparse group Lasso.

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来源期刊
Genomics and Informatics
Genomics and Informatics Agricultural and Biological Sciences-Ecology, Evolution, Behavior and Systematics
CiteScore
1.90
自引率
0.00%
发文量
0
审稿时长
12 weeks
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