plot_hexbin_interact: Plot of interaction of expression of single cells in...
In schex: Hexbin plots for single cell omics data

Description Usage Arguments Details Value Examples

Plot of interaction of expression of single cells in bivariate hexagon cells.

plot_hexbin_interact(
  sce,
  mod,
  type,
  feature,
  interact,
  title = NULL,
  xlab = NULL,
  ylab = NULL
)

`sce`	A `SingleCellExperiment` or `Seurat-class` object.
`mod`	A vector of strings referring to the names of the modularities. For `SingleCellExperiment` use "RNA" to access the RNA expression data stored as the main experiment type.
`type`	A vector of strings referring to the types of assays in the `SingleCellExperiment` or the types of transformation in `Seurat-class` object.
`feature`	A vector of strings referring to the names of one features in the same order as the vector of modularities.
`interact`	A string specifying how interaction between features is calculated. Possible interaction measures are `corr_spearman` and `mi` (see details).
`title`	A string containing the title of the plot.
`xlab`	A string containing the title of the x axis.
`ylab`	A string containing the title of the y axis.

This function plots the interaction between any features in the hexagon cell representation calculated with make_hexbin. The interaction between the chosen features is calculated by one of two measurers corr_spearman, ratio and mi:

mi: Returns the mutual information coefficient.
corr_spearman: Returns the Spearman correlation.
fc: Return the log fold change between the features.

Note that fc should be applied to log normalized values.

A ggplot2{ggplot} object.

# For Seurat object
library(Seurat)
data("pbmc_small")
pbmc_small <- make_hexbin(pbmc_small, 10, dimension_reduction = "PCA")
protein <- matrix(rnorm(10 * ncol(pbmc_small)), ncol = ncol(pbmc_small))
rownames(protein) <- paste0("A", seq(1, 10, 1))
colnames(protein) <- colnames(pbmc_small)
pbmc_small[["ADT"]] <- CreateAssayObject(counts = protein)
plot_hexbin_interact(pbmc_small, type=c("counts", "counts"),
    mod=c("RNA", "ADT"), feature=c("CD7", "A1"), interact="mi")