newSlingshotDataSet {slingshot} | R Documentation

## Initialize an object of class `SlingshotDataSet`

### 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.clus`character. The label of the root cluster. `end.clus`character. Vector of cluster labels indicating the 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 `dist`matrix. A numeric matrix of pairwise cluster distances. They may also specify how simultaneous principal curves were constructed: `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. 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)

[Package slingshot version 1.6.1 Index]