make_hexbin {schex} | R Documentation

## Bivariate binning of single cell data into hexagon cells.

### Description

`make_hexbin` returns a `SingleCellExperiment` or `Seurat-class` object of binned hexagon cells.

### Usage

    make_hexbin(sce, nbins = 80, dimension_reduction = "UMAP", use_dims = c(1, 2))

    ## S4 method for signature 'SingleCellExperiment'
    make_hexbin(sce, nbins = 80, dimension_reduction = "UMAP", use_dims = c(1, 2))

    ## S4 method for signature 'Seurat'
    make_hexbin(sce, nbins = 80, dimension_reduction = "UMAP", use_dims = c(1, 2))

### Arguments

`sce` | A `SingleCellExperiment` or `Seurat-class` object.
`nbins` | The number of bins partitioning the range of the first component of the chosen dimension reduction.
`dimension_reduction` | A string indicating the reduced dimension result to calculate hexagon cell representation of.
`use_dims` | A vector of two integers specifying the dimensions used.

### Details

This function bins observations with computed reduced dimension results into hexagon cells. For a `Seurat-class` object the results from this function are stored in `@misc`. For a `SingleCellExperiment` as a list in the `@metadata`. The list contains two items. The first item stores a vector specifying the hexagon ID for each observation. The second item stores a matrix with the x and y positions of the hexagon cells and the number of observations in each of them.

### Value

A `SingleCellExperiment` or `Seurat-class` object.

### Functions

- `make_hexbin,SingleCellExperiment-method`: Bivariate binning of SingleCellExperiment into hexagon cells.

- `make_hexbin,Seurat-method`: Bivariate binning of Seurat into hexagon cells.

### Examples

    # For Seurat object
    library(Seurat)
    data("pbmc_small")
    pbmc_small <- make_hexbin(pbmc_small, 10, dimension_reduction = "PCA")
    # For SingleCellExperiment object
    ## Not run:
    library(TENxPBMCData)
    library(scater)
    tenx_pbmc3k <- TENxPBMCData(dataset = "pbmc3k")
    rm_ind <- calculateAverage(tenx_pbmc3k) < 0.1
    tenx_pbmc3k <- tenx_pbmc3k[!rm_ind, ]
    tenx_pbmc3k <- logNormCounts(tenx_pbmc3k)
    tenx_pbmc3k <- runPCA(tenx_pbmc3k)
    tenx_pbmc3k <- make_hexbin(tenx_pbmc3k, 80, dimension_reduction = "PCA")

    ## End(Not run)

[Package schex version 1.8.0 Index]