Description Usage Arguments Details Value Author(s) References See Also Examples
Method visualizes an approximation of the manifold in the latent space in two dimensions.
1 2 3 4 5 6 7 | plotManifold(
sce,
color_by = c("phenoName", "featureName"),
name,
perplexity = 30,
recalculate = FALSE
)
|
sce |
A |
color_by |
Indicates if nodes are colorized by a feature expression ('featureName') or phenotype label ('phenoName') |
name |
A character string specifying the featureName or phenoName |
perplexity |
Perplexity parameter for tSNE computation (default: 30) |
recalculate |
Indicates if tSNE should be recalcuated and results returned (default: FALSE) |
Visualizes the learned lower-dimensional manifold in two dimensions
using an approximation obtained by Barnes-Hut implementation of
t-Distributed Stochastic Neighbor Embedding
(tSNE; van der Maaten and Hinton 2008). Each point in this plot represents
a sample. Points can be colorized according
to feature expression or experimental metadata. The points' coloration can
be defined via the attributes color_by
and name
,
respectively. A previously computed tSNE visualization will be reused if
it was set accordingly (see manifold2D<-
). The parameter
perplexity
is used for the tSNE calculation.
A ggplot
object
Daniel C. Ellwanger
van der Maaten, L.J.P. & Hinton, G.E., 2008. Visualizing High-Dimensional Data Using t-SNE. Journal of Machine Learning Research, 9, pp.2579-2605.
1 2 3 4 5 6 7 | # Example data
data(exSCE)
plotManifold(exSCE, color_by="featureName", name="feature_10")
gp <- plotManifold(exSCE, color_by="phenoName", name="age",
recalculate=TRUE)
manifold2D(exSCE) <- gp
|
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