{ "_id": "6a1ad3631d7bb097a09e38db", "Package": "escheR", "Title": "Unified multi-dimensional visualizations with Gestalt principles", "Version": "1.13.0", "Authors@R": "c(\nperson(\"Boyi\", \"Guo\",\nemail = \"boyi.guo.work@gmail.com\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-2950-2349\")),\nperson(c(\"Stephanie\", \"C.\"), \"Hicks\", role = c(\"aut\"),\nemail = \"shicks19@jhu.edu\",\ncomment = c(ORCID = \"0000-0002-7858-0231\")),\nperson(c(\"Erik\", \"D.\"), \"Nelson\",\nemail = \"erik.nelson116@gmail.com\", role = c(\"ctb\"),\ncomment = c(ORCID = \"0000-0001-8477-0982\"))\n)", "Description": "The creation of effective visualizations is a fundamental\ncomponent of data analysis. In biomedical research, new\nchallenges are emerging to visualize multi-dimensional data in\na 2D space, but current data visualization tools have limited\ncapabilities. To address this problem, we leverage Gestalt\nprinciples to improve the design and interpretability of\nmulti-dimensional data in 2D data visualizations, layering\naesthetics to display multiple variables. The proposed\nvisualization can be applied to spatially-resolved\ntranscriptomics data, but also broadly to data visualized in 2D\nspace, such as embedding visualizations. 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