{"title":"MP-LASSO图:用于可视化基因组数据组LASSO分析的多级极坐标图。","authors":"Min Song, Minhyuk Lee, Taesung Park, Mira Park","doi":"10.5808/gi.22075","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":36591,"journal":{"name":"Genomics and Informatics","volume":"20 4","pages":"e48"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9847381/pdf/","citationCount":"0","resultStr":"{\"title\":\"MP-LASSO chart: a multi-level polar chart for visualizing group LASSO analysis of genomic data.\",\"authors\":\"Min Song, Minhyuk Lee, Taesung Park, Mira Park\",\"doi\":\"10.5808/gi.22075\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":36591,\"journal\":{\"name\":\"Genomics and Informatics\",\"volume\":\"20 4\",\"pages\":\"e48\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9847381/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Genomics and Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5808/gi.22075\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Agricultural and Biological Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genomics and Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5808/gi.22075","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
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.