feat {cellpypes}

Feature plots: Color gene expression in 2D embeddings

Description

Highlight gene expression in UMAP embeddings, for example.

Usage

feat(obj, features, fast = NULL, verbose = TRUE, ...)

Arguments

obj

A cellpypes object, see section cellpypes Objects below.

features

A vector of genes (features) to colour by.

fast

Set this to TRUE if you want fast plotting in spite of many cells (using the scattermore package). If NULL (default), cellpypes decides automatically and fast plotting is done for more than 10k cells, if FALSE it always uses geom_point.

verbose

feat ignores gene names not present in your object and warns you about them by default. verbose=FALSE will suppress the warning (not recommended in interactive use).

...

Arguments passed to cowplot's plot_grid function, for example ncol or rel_widths.

Value

A ggplot object (assembled by cowplot).

cellpypes Objects

A cellpypes object is a list with four slots:

raw

(sparse) matrix with genes in rows, cells in columns

totalUMI

the colSums of obj$raw

embed

two-dimensional embedding of the cells, provided as data.frame or tibble with two columns and one row per cell.

neighbors

index matrix with one row per cell and k columns, where k is the number of nearest neighbors (we recommend 15<k<100, e.g. k=50). Here are two ways to get the neighbors index matrix:

• Use find_knn(featureMatrix)$idx, where featureMatrix could be principal components, latent variables or normalized genes (features in rows, cells in columns).

• use as(seurat@graphs[["RNA_nn"]], "dgCMatrix")> .1 to extract the kNN graph computed on RNA. The > .1 ensures this also works with RNA_snn, wknn/wsnn or any other available graph – check with names(seurat@graphs).

Examples

feat(simulated_umis, "CD3E")