slingshot (version 2.1.1)

SlingshotDataSet-class: Class SlingshotDataSet

Description

This was the original class for storing slingshot results, but we now generally reommend using the PseudotimeOrdering class, instead. Most slingshot functions will still work with SlingshotDataSet objects, but will return PseudotimeOrdering objects, by default. To update old SlingshotDataSet objects, we have provided the as.PseudotimeOrdering conversion function. The only functions that require SlingshotDataSet objects are the plotting functions.

The SlingshotDataSet class holds data relevant for performing lineage inference with the slingshot package, primarily a reduced dimensional representation of the data and a set of cluster labels.

Usage

# S4 method for SlingshotDataSet
show(object)
# S4 method for SlingshotDataSet,ANY
reducedDim(x)
# S4 method for SlingshotDataSet
reducedDims(x)

Arguments

object

a SlingshotDataSet object.

x

a SlingshotDataSet object.

Value

The accessor functions reducedDim, clusterLabels, lineages, adjacency, curves, and slingParams return the corresponding elements of a SlingshotDataSet. The functions slingPseudotime and slingCurveWeights extract useful output elements of a SlingshotDataSet, provided that curves have already been fit with either slingshot or getCurves.

Methods (by generic)

• show: a short summary of a SlingshotDataSet object.

• reducedDim: returns the matrix representing the reduced dimensional dataset.

Slots

reducedDim

matrix. An n by p numeric matrix or data frame giving the coordinates of the cells in a reduced dimensionality space.

clusterLabels

matrix or character. An n by K matrix of weights indicating each cell's cluster assignment or a character vector of cluster assignments, which will be converted into a binary matrix.

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 adjacency 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.clus character. The label of the root cluster, or a vector of cluster labels giving the root clusters of each disjoint component of the graph.

• end.clus character. Vector of cluster labels indicating terminal clusters.

• start.given logical. A logical value indicating whether the initial state was pre-specified.

• end.given logical. A vector of logical values indicating whether each terminal state was pre-specified

• omega numeric or logical. Granularity parameter determining the maximum edge length for building the MST. See getLineages.

• omega_scale numeric. Scaling factor used for setting maximum edge length when omega = TRUE. See getLineages.

They may also specify how simultaneous principal curves were constructed (for a complete listing, see getCurves:

• shrink logical or numeric between 0 and 1. Determines whether and how much to shrink branching lineages toward their shared average curve.

• extend character. 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.

• reweight logical. 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.

• reassign logical. 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.method character. 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.

• approx_points numeric. Number of points to use in estimating curves. See getCurves for details.

• allow.breaks logical. Whether to allow curves that diverge very early on in a trajectory to have different starting points.

• Other parameters specified by principal_curve.

See Also

PseudotimeOrdering