reduce_dimensionality: Dimensionality reduction

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

Description

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

Usage

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

Arguments

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.

Value

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

See Also

SCORPIUS

Examples

## 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)

SCORPIUS documentation built on June 9, 2021, 5:07 p.m.