View source: R/cytof_dimensionReduction.R
cytof_dimReduction | R Documentation |
Apply dimension reduction on the cytof expression data,
with method pca
, tsne
, umap
or isomap
.
cytof_dimReduction( data, markers = NULL, method = c("umap", "tsne", "pca", "isomap", "NULL"), distMethod = "euclidean", out_dim = 2, umap_neighbor = 30, umap_min_dist = 0.3, tsneSeed = 42, isomap_k = 5, isomap_ndim = NULL, isomapFragmentOK = TRUE, ... )
data |
Input expression data matrix. |
markers |
Selected markers for dimension reduction, either marker names/descriptions or marker IDs. |
method |
Method chosen for dimensition reduction, must be one of |
distMethod |
Method for distance calcualtion, default is "euclidean", other choices like "manhattan", "cosine", "rankcor".... |
out_dim |
The dimensionality of the output. |
umap_neighbor |
This parameter controls how UMAP balances local versus global structure in the data. |
umap_min_dist |
Controls how tightly UMAP is allowed to pack points together. |
tsneSeed |
Set a seed if you want reproducible t-SNE results. |
isomap_k |
Number of shortest dissimilarities retained for a point, parameter for |
isomap_ndim |
Number of axes in metric scaling, parameter for |
isomapFragmentOK |
What to do if dissimilarity matrix is fragmented, parameter for |
... |
Other parameters passed to the method, check |
A matrix of the dimension reduced data, with colnames method_ID, and rownames same as the input data.
data(iris) in_data <- iris[, 1:4] markers <- colnames(in_data[, 1:4]) out_data <- cytof_dimReduction(in_data, markers = markers, method = "tsne")
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