View source: R/dim.reduction.R
dim.reduction | R Documentation |
It calculates a dimensional reduction (DR) from a fcs.SCE
object (or an expression table). Three different DR methods are available: Principal Component Analsis (PCA), t-Distributed Stochastic Neighbor Embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP).
## S3 method for class 'reduction'
dim(
data,
assay.i = "normalized",
markers.to.use = "all",
dr.method,
num.threads = NULL,
perplexity.tsne = 100,
n.neighbors.umap = 50
)
data |
A |
assay.i |
Name of matrix stored in the |
markers.to.use |
Markers to take account in the DR calculus. Default = |
dr.method |
DR method to calculate. Possible values are "PCA", "tSNE", "DENSNE", "UMAP" and/or "DENSMAP". If PCA is calculated, rotation values are also stored in the 'fcs.SCE@metadata' (or separatelly if 'data' is a 'data.frame' instead a 'fcs.SCE' object). |
num.threads |
Number of threads for DR calculus. If |
perplexity.tsne |
Value for perplexity parameter in tSNE calculation (more information). Default = |
n.neighbors.umap |
Value for neighbors parameter in UMAP calculation (more information). Default = |
## Not run:
fcs <- dim.reduction(fcs, dr.method = "tSNE",
markers.to.use = c("CD8", "CD27", "CCR4", "CD45RA", "CD4"))
fcs <- dim.reduction(fcs, dr.method = "UMAP", n.neighbors.umap = 10)
fcs <- dim.reduction(fcs, dr.method = c("pca", "Umap"))
## End(Not run)
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