newSlingshotDataSet: Initialize an object of class 'SlingshotDataSet'

In slingshot: Tools for ordering single-cell sequencing

Description

Constructs a SlingshotDataSet object. Additional helper methods for manipulating SlingshotDataSet objects are also described below.

Usage

newSlingshotDataSet(reducedDim, clusterLabels, ...)

## S4 method for signature 'data.frame,ANY'
newSlingshotDataSet(reducedDim, clusterLabels, ...)

## S4 method for signature 'matrix,numeric'
newSlingshotDataSet(reducedDim, clusterLabels, ...)

## S4 method for signature 'matrix,factor'
newSlingshotDataSet(reducedDim, clusterLabels, ...)

## S4 method for signature 'matrix,ANY'
newSlingshotDataSet(reducedDim, clusterLabels, ...)

## S4 method for signature 'matrix,character'
newSlingshotDataSet(reducedDim, clusterLabels, ...)

## S4 method for signature 'matrix,matrix'
newSlingshotDataSet(
  reducedDim,
  clusterLabels,
  lineages = list(),
  adjacency = matrix(NA, 0, 0),
  curves = list(),
  slingParams = list()
)

Arguments

reducedDim	matrix. An n by p numeric matrix or data frame giving the coordinates of the cells in a reduced dimensionality space.
clusterLabels	character. A character vector of length n denoting each cell's cluster label.
...	additional components of a SlingshotDataSet to specify. This may include any of the following:
lineages	list. A list with each element a character vector of cluster names representing a lineage as an ordered set of clusters.
adjacency	matrix. A binary matrix describing the connectivity between clusters induced by the minimum spanning tree.
curves	list. A list of principal_curve objects produced by getCurves.
slingParams	list. Additional parameters used by Slingshot. These may specify how the minimum spanning tree on clusters was constructed: start.cluscharacter. The label of the root cluster. end.cluscharacter. Vector of cluster labels indicating the terminal clusters. start.givenlogical. A logical value indicating whether the initial state was pre-specified. end.givenlogical. A vector of logical values indicating whether each terminal state was pre-specified distmatrix. A numeric matrix of pairwise cluster distances. They may also specify how simultaneous principal curves were constructed: shrinklogical or numeric between 0 and 1. Determines whether and how much to shrink branching lineages toward their shared average curve. extendcharacter. Specifies the method for handling root and leaf clusters of lineages when constructing the initial, piece-wise linear curve. Accepted values are 'y' (default), 'n', and 'pc1'. See getCurves for details. reweightlogical. Indicates whether to allow cells shared between lineages to be reweighted during curve-fitting. If TRUE, cells shared between lineages will be iteratively reweighted based on the quantiles of their projection distances to each curve. reassignlogical. Indicates whether to reassign cells to lineages at each iteration. If TRUE, cells will be added to a lineage when their projection distance to the curve is less than the median distance for all cells currently assigned to the lineage. Additionally, shared cells will be removed from a lineage if their projection distance to the curve is above the 90th percentile and their weight along the curve is less than 0.1. shrink.methodcharacter. Denotes how to determine the amount of shrinkage for a branching lineage. Accepted values are the same as for kernel in the density function (default is "cosine"), as well as "tricube" and "density". See getCurves for details. Other parameters specified by principal_curve.

Value

A SlingshotDataSet object with all specified values.

Functions

• newSlingshotDataSet,data.frame,ANY-method: returns a SlingshotDataSet object.

• newSlingshotDataSet,matrix,numeric-method: returns a SlingshotDataSet object.

• newSlingshotDataSet,matrix,factor-method: returns a SlingshotDataSet object.

• newSlingshotDataSet,matrix,ANY-method: returns a SlingshotDataSet object.

• newSlingshotDataSet,matrix,character-method: returns a SlingshotDataSet object.

• newSlingshotDataSet,matrix,matrix-method: returns a SlingshotDataSet object.

Examples

rd <- matrix(data=rnorm(100), ncol=2)
cl <- sample(letters[seq_len(5)], 50, replace = TRUE)
sds <- newSlingshotDataSet(rd, cl)

slingshot documentation built on Nov. 8, 2020, 5:51 p.m.