SlingshotDataSet-class {slingshot} | R Documentation

## Class `SlingshotDataSet`

### Description

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. All `slingshot` methods can take an object of the class `SlingshotDataSet` as input and will output the same.

Extract cluster labels, either a character vector or matrix of weights.

# replacement methods

### Usage

    ## S4 method for signature 'SlingshotDataSet'
    show(object)

    ## S4 method for signature 'SlingshotDataSet'
    reducedDim(x)

    ## S4 method for signature 'SlingshotDataSet'
    reducedDims(x)

    ## S4 method for signature 'SlingshotDataSet'
    clusterLabels(x)

    ## S4 method for signature 'SlingshotDataSet,ANY,ANY,ANY'
    x[i, j]

### Arguments

`object` | a `SlingshotDataSet` object.
`x` | a `SlingshotDataSet` object.
`i` | indices to be applied to rows (cells) of the reduced dimensional matrix and cluster labels.
`j` | indices to be applied to the columns (dimensions) of the reduced dimensional matrix.

### Details

Warning: this will remove any existing lineages or curves from the `SlingshotDataSet` object.

### Value

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

A matrix of cluster weights for each cell or a vector of cluster assignments.

### Methods (by generic)

- `show`: a short summary of `SlingshotDataSet` object.

- `reducedDim`: returns the matrix representing the reduced dimensional dataset.

- `reducedDims`: returns the matrix representing the reduced dimensional dataset.

- `clusterLabels`: extracts cluster labels from a `SlingshotDataSet` object.

- `[`: Subset dataset and cluster labels.

### 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.

  - `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`.

### Examples

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

[Package slingshot version 1.0.0 Index]