findCurves-methods: Find pseudo-time curves.

In edroaldo/fusca: Framework for Unified Single-Cell Analysis

Find pseudo-time curves.

Description

Find pseudo-time curves using the princurve library. Alternative to the findPaths method. Add to CellRouter@curves a list with the cells, their distance from the origin of the curve, and the population they belong, for each path curve.

Usage

findCurves(
  object,
  assay.type = "RNA",
  column = "population",
  population_sequences = list(),
  find_populations = FALSE,
  sources = NULL,
  targets = NULL,
  dims.use,
  reduction.type
)

## S4 method for signature 'CellRouter'
findCurves(
  object,
  assay.type = "RNA",
  column = "population",
  population_sequences = list(),
  find_populations = FALSE,
  sources = NULL,
  targets = NULL,
  dims.use,
  reduction.type
)

Arguments

object	CellRouter object.
assay.type	character; the type of data to use.
column	character; column in the metadata table specifying whether transitions are between clusters or other annotations, such as sorted populations.
population_sequences	list of character vectors; the ordered sequence of the populations that will be used to calculate the curve.
find_populations	boolean; if TRUE, the population sequence will be found by the algorithm given a source and target population, if FALSE, the population sequence will be specified by the user.
sources	character vector; name of the source population.
targets	character vector; name of the target population.
dims.use	numeric vector; the number of dimensions to use.
reduction.type	character; the dimension reduction space to be used: pca, tsne, DC of diffusion components, umap, or custom.

Value

CellRouter object with the curves slot updated.

edroaldo/fusca documentation built on March 1, 2023, 1:43 p.m.