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Plot NMF topic profiles

Source: R/plotTopicProfiles.R
plotTopicProfiles.Rd

This function takes in the fitted NMF model and returns the topic profiles learned for each cell facet = FALSE or cell type facet = TRUE. Ideal training will return all the cell from the same cell type to share a unique topic profile.

Usage

# S4 method for NMF,ANY
plotTopicProfiles(x, y, ...)

# S4 method for NMF,character
plotTopicProfiles(x, y, facet = FALSE, min_prop = 0.1, ncol = NULL)

Arguments

x

NMFfit object

y

vector of group labels. Should be of length ncol(coef(x)).

...

additional parameters

facet

logical indicating whether to stratify by group. If FALSE (default), weights will be the median across cells for each group (point = topic weight for a given cell type). If TRUE, cell-specific weights will be shown (point = topic weight of a given cell).

min_prop

scalar in [0,1]. When facet = TRUE, only cells with a weight > min_prop will be included.

ncol

integer scalar specifying the number of facet columns.

Value

ggplot object

Author

Marc Elosua Bayes & Helena L Crowell

Examples

library(ggplot2)
x <- .mock_sc()
y <- .mock_sp(x)
z <- .get_mgs(x)

res <- SPOTlight(x, y,
    groups = x$type,
    mgs = z,
    group_id = "type",
    verbose = FALSE)

plotTopicProfiles(res[[3]], x$type, facet = TRUE)

plotTopicProfiles(res[[3]], x$type, facet = FALSE)