Package: escheR 1.5.0

Boyi Guo

escheR: Unified multi-dimensional visualizations with Gestalt principles

The creation of effective visualizations is a fundamental component of data analysis. In biomedical research, new challenges are emerging to visualize multi-dimensional data in a 2D space, but current data visualization tools have limited capabilities. To address this problem, we leverage Gestalt principles to improve the design and interpretability of multi-dimensional data in 2D data visualizations, layering aesthetics to display multiple variables. The proposed visualization can be applied to spatially-resolved transcriptomics data, but also broadly to data visualized in 2D space, such as embedding visualizations. We provide this open source R package escheR, which is built off of the state-of-the-art ggplot2 visualization framework and can be seamlessly integrated into genomics toolboxes and workflows.

Authors:Boyi Guo [aut, cre], Stephanie C. Hicks [aut], Erik D. Nelson [ctb]

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escheR.pdf |escheR.html✨
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Bug tracker:https://github.com/boyiguo1/escher/issues

On BioConductor:escheR-1.5.0(bioc 3.20)escheR-1.4.0(bioc 3.19)

bioconductor-package

6 exports 1.31 score 78 dependencies 1 dependents

Last updated 2 months agofrom:f8f3dab3b0

Exports:add_filladd_fill_binadd_groundadd_ground_binadd_symbolmake_escheR

Dependencies:abindaskpassBiobaseBiocFileCacheBiocGenericsbitbit64blobcachemclicolorspacecpp11crayoncurlDBIdbplyrDelayedArraydplyrfansifarverfastmapfilelockgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2gluegtablehttrIRangesisobandjsonlitelabelinglatticelifecyclemagickmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimemunsellnlmeopensslpillarpkgconfigplogrpurrrR6RColorBrewerRcpprjsonrlangRSQLiteS4ArraysS4VectorsscalesSingleCellExperimentSparseArraySpatialExperimentstringistringrSummarizedExperimentsystibbletidyrtidyselectUCSC.utilsutf8vctrsviridisLitewithrXVectorzlibbioc