reduce_dimensionality: Dimensionality reduction
In SCORPIUS: Inferring Developmental Chronologies from Single-Cell RNA Sequencing Data

Description Usage Arguments Value See Also Examples

View source: R/dimensionality_reduction.R

reduce_dimensionality performs an eigenanalysis of the given dissimilarity matrix and returns coordinates of the samples represented in an ndim-dimensional space.

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reduce_dimensionality(x, dist = c("pearson", "spearman", "cosine",
  "euclidean", "manhattan"), ndim = 3, num_landmarks = 1000,
  rescale = TRUE)

`x`	a numeric matrix
`dist`	the distance metric to be used; can be any of the metrics listed in `dynutils::calculate_distance()`.
`ndim`	the maximum dimension of the space which the data are to be represented in; must be in 1, 2, ..., n-1.
`num_landmarks`	the number of landmarks to be selected.
`rescale`	A logical indicating whether or not the returned space should be rescaled and centered.

A matrix containing the coordinates of each sample, represented in an ndim-dimensional space.

SCORPIUS

## Generate an example dataset
dataset <- generate_dataset(num_genes = 500, num_samples = 1000, num_groups = 4)

## Reduce the dimensionality of this dataset
space <- reduce_dimensionality(dataset$expression, ndim = 2)

## Visualise the dataset
draw_trajectory_plot(space, progression_group = dataset$sample_info$group_name)