| make_hexbin {schex} | R Documentation |
make_hexbin returns a
SingleCellExperiment or
Seurat-class object of binned hexagon cells.
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))
sce |
A |
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. |
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.
A SingleCellExperiment or
Seurat-class object.
SingleCellExperiment: Bivariate binning of SingleCellExperiment
into hexagon cells.
Seurat: Bivariate binning of Seurat
into hexagon cells.
# 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 <- normalize(tenx_pbmc3k)
tenx_pbmc3k <- runPCA(tenx_pbmc3k)
tenx_pbmc3k <- make_hexbin( tenx_pbmc3k, 80, dimension_reduction = "PCA")
## End(Not run)