All functions |
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Add analysis data from a 10x Genomics Visium experiment to a SPE object |
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Add non-standard images with the same dimensions as current ones |
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Create a unique spot identifier |
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Quality Control for Spatial Data |
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Annotated spatially-registered clusters |
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Check input modeling_results |
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Check input sce |
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Check input sce_layer |
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Check input spe |
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Export a column with cluster results |
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Import cluster results |
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Determine if you have enough RAM memory |
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Download the Human DLPFC Visium data from LIBD |
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Identify the image limits |
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Evaluate the enrichment for a list of gene sets |
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Plot the gene set enrichment results with ComplexHeatmap |
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A ggplot2 layer for visualizing the Visium histology |
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Obtain the colors for a set of cluster names |
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Edit a background image |
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Update the image for one sample |
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Update the images for all samples |
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Layer-level (group-level) boxplots |
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Layer modeling correlation of statistics |
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Visualize the correlation of layer modeling t-statistics with ComplexHeatmap |
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Vector of LIBD layer colors |
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Locate image files |
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Load analysis data from a 10x Genomics Visium experiment |
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Load data from a 10x Genomics Visium experiment and make it spatialLIBD-ready |
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Spatial registration: block correlation |
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Spatial registration: model |
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Spatial registration: pseudobulk |
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Spatial registration: compute ANOVA statistics |
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Spatial registration: compute enrichment statistics |
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Spatial registration: compute pairwise statistics |
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Spatial registration: wrapper function |
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Run the spatialLIBD Shiny Application |
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Convert a SCE object to a SPE one |
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Extract significant genes |
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Extract significant genes for all modeling results |
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Sort clusters by frequency |
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Cell cluster t-statistics from Tran et al |
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Sample spatial cluster visualization |
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Sample spatial cluster visualization workhorse function |
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Sample spatial gene visualization |
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Sample spatial gene visualization workhorse function |
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Sample spatial cluster visualization grid |
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Sample spatial gene visualization grid |