Monocle3 aims to learn how cells transition through a
biological program of gene expression changes in an experiment. Each cell
can be viewed as a point in a high-dimensional space, where each dimension
describes the expression of a different gene. Identifying the program of
gene expression changes is equivalent to learning a trajectory that
the cells follow through this space. However, the more dimensions there are
in the analysis, the harder the trajectory is to learn. Fortunately, many
genes typically co-vary with one another, and so the dimensionality of the
data can be reduced with a wide variety of different algorithms. Monocle3
provides two different algorithms for dimensionality reduction via
reduce_dimension (UMAP and tSNE). The function
reduce_dimension is the second step in the trajectory building
process after preprocess_cds.
UMAP is implemented from the package uwot.
reduce_dimension(
cds,
max_components = 2,
reduction_method = c("UMAP", "tSNE", "PCA", "LSI", "Aligned"),
preprocess_method = NULL,
umap.metric = "cosine",
umap.min_dist = 0.1,
umap.n_neighbors = 15L,
umap.fast_sgd = FALSE,
umap.nn_method = "annoy",
cores = 1,
verbose = FALSE,
...
)the cell_data_set upon which to perform this operation.
the dimensionality of the reduced space. Default is 2.
A character string specifying the algorithm to use for dimensionality reduction. Currently "UMAP", "tSNE", "PCA", "LSI", and "Aligned" are supported.
A string indicating the preprocessing method used on the data. Options are "PCA" and "LSI". Default is "LSI".
A string indicating the distance metric to be used when
calculating UMAP. Default is "cosine". See uwot package's
umap for details.
Numeric indicating the minimum distance to be passed to
UMAP function. Default is 0.1.See uwot package's umap
for details.
Integer indicating the number of neighbors to use
during kNN graph construction. Default is 15L. See uwot package's
umap for details.
Logical indicating whether to use fast SGD. Default is
TRUE. See uwot package's umap for details.
String indicating the nearest neighbor method to be
used by UMAP. Default is "annoy". See uwot package's
umap for details.
Number of compute cores to use.
Logical, whether to emit verbose output.
additional arguments to pass to the dimensionality reduction function.
an updated cell_data_set object
UMAP: McInnes, L, Healy, J, UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction, ArXiv e-prints 1802.03426, 2018
tSNE: Laurens van der Maaten and Geoffrey Hinton. Visualizing data using t-SNE. J. Mach. Learn. Res., 9(Nov):2579<U+2013> 2605, 2008.