SpatialFeatureExperiment - Integrating SpatialExperiment with Simple Features in sf
A new S4 class integrating Simple Features with the R package sf to bring geospatial data analysis methods based on vector data to spatial transcriptomics. Also implements management of spatial neighborhood graphs and geometric operations. This pakage builds upon SpatialExperiment and SingleCellExperiment, hence methods for these parent classes can still be used.
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datarepresentationtranscriptomicsspatial
10.04 score 57 stars 2 dependents 710 scripts 772 downloadsVoyager - From geospatial to spatial omics
SpatialFeatureExperiment (SFE) is a new S4 class for working with spatial single-cell genomics data. The voyager package implements basic exploratory spatial data analysis (ESDA) methods for SFE. Univariate methods include univariate global spatial ESDA methods such as Moran's I, permutation testing for Moran's I, and correlograms. Bivariate methods include Lee's L and cross variogram. Multivariate methods include MULTISPATI PCA and multivariate local Geary's C recently developed by Anselin. The Voyager package also implements plotting functions to plot SFE data and ESDA results.
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geneexpressionspatialtranscriptomicsvisualizationbioconductoredaesdaexploratory-data-analysisomicsspatial-statisticsspatial-transcriptomics
8.94 score 103 stars 422 scriptswompwomp - Optimizing Alluvial Plots
Sort k-partite graphs with node order, layer order, and node grouping optimized with a heuristic to (nearly) minimize edge crossings. Useful for improving visualizations with alluvial plots by "untangling" the graphs.
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7.22 score 31 stars 5 scripts 247 downloadsconcordexR - Identify Spatial Homogeneous Regions with concordex
Spatial homogeneous regions (SHRs) in tissues are domains that are homogenous with respect to cell type composition. We present a method for identifying SHRs using spatial transcriptomics data, and demonstrate that it is efficient and effective at finding SHRs for a wide variety of tissue types. concordex relies on analysis of k-nearest-neighbor (kNN) graphs. The tool is also useful for analysis of non-spatial transcriptomics data, and can elucidate the extent of concordance between partitions of cells derived from clustering algorithms, and transcriptomic similarity as represented in kNN graphs.
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singlecellclusteringspatialtranscriptomics
7.03 score 15 stars 178 scripts 302 downloadsalabaster.sfe - Language agnostic on disk serialization of SpatialFeatureExperiment
Builds upon the existing ArtifactDB project, expending alabaster.spatial for language agnostic on disk serialization of SpatialFeatureExperiment.
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datarepresentationspatialopenjdk
5.40 score 252 scripts 186 downloads