Cross-Expression Analysis of Spatial Transcriptomics Data

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Documentation for package ‘CrossExpression’ version 1.0.0

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bullseye_plot Outputs a circular bullseye plot for a gene pair. The central circle is gene B in cells expressing gene A. Rings indicate neighbors with gene B, where the first ring is the first neighbor.
bullseye_scores Calculates bullseye statistics for ALL gene pairs. Counts the number of cells with gene B in those with gene A And in their neighbors Neighbor scores are cumulative and normalized by window size.
correlation Computes Pearson's correlation between pairs of columns. If one matrix is provided, the output is the pairwise correlations between its columns. If two matrices are provided, the output is the pairwise correlations between their columns.
cross_expression Computes cross-expression and co-expression p-values between all gene pairs.
cross_expression_correlation Computes gene-gene correlations between cross-expressing cell-neighbor pairs. Cell and neighbor masks are used to consider mutually exclusive expression per gene pair.
expression Example gene expression matrix
get_cooccurrence_stats Calculates the number of elements common between columns of two matrices. This function performs a simple dot product when binarize = FALSE.
locations Example cell location matrix
rotate_coordinates This function takes x and y coordinates and rotates them counterclockwise by the specified number of degrees, and mean centers the points.
smooth_cells Smooths cells' gene expression by averaging its expression by the nearest neighbors. Optionally computes genes by genes Pearson's correlation matrix between cells by genes and neighbors by genes matrices.
spatial_enrichment Determines whether the supplied genes show spatial enrichment in cross-expression. Spatial enrichment can be interpreted as delineating anatomical boundaries.
tissue_expression_plot Plots gene expression and cross-expression on tissue by coloring cells.