buildSNNGraph {scran} | R Documentation

## Build a nearest-neighbor graph

### Description

SingleCellExperiment-friendly wrapper around the `makeSNNGraph` and `makeKNNGraph` functions for creating nearest-neighbor graphs.

### Usage

    buildSNNGraph(x, ...)

    ## S4 method for signature 'ANY'
    buildSNNGraph(
      x,
      ...,
      d = 50,
      transposed = FALSE,
      subset.row = NULL,
      BSPARAM = bsparam(),
      BPPARAM = SerialParam()
    )

    ## S4 method for signature 'SummarizedExperiment'
    buildSNNGraph(x, ..., assay.type = "logcounts")

    ## S4 method for signature 'SingleCellExperiment'
    buildSNNGraph(x, ..., use.dimred = NULL)

    buildKNNGraph(x, ...)

    ## S4 method for signature 'ANY'
    buildKNNGraph(
      x,
      ...,
      d = 50,
      transposed = FALSE,
      subset.row = NULL,
      BSPARAM = bsparam(),
      BPPARAM = SerialParam()
    )

    ## S4 method for signature 'SingleCellExperiment'
    buildKNNGraph(x, ..., use.dimred = NULL)

    ## S4 method for signature 'SingleCellExperiment'
    buildKNNGraph(x, ..., use.dimred = NULL)

### Arguments

`x` | A matrix-like object containing expression values for each gene (row) in each cell (column). These dimensions can be transposed if `transposed=TRUE`. Alternatively, a SummarizedExperiment or SingleCellExperiment containing such an expression matrix. If `x` is a SingleCellExperiment and `use.dimred` is set, its `reducedDims` will be used instead.
`...` | For the generics, additional arguments to pass to the specific methods. For the ANY methods, additional arguments to pass to `makeSNNGraph` or `makeKNNGraph`. For the SummarizedExperiment methods, additional arguments to pass to the corresponding ANY method. For the SingleCellExperiment methods, additional arguments to pass to the corresponding SummarizedExperiment method.
`d` | An integer scalar specifying the number of dimensions to use for a PCA on the expression matrix prior to the nearest neighbor search. Ignored for the ANY method if `transposed=TRUE` and for the SingleCellExperiment methods if `use.dimred` is set.
`transposed` | A logical scalar indicating whether `x` is transposed (i.e., rows are cells).
`subset.row` | See `?"scran-gene-selection"`. Only used when `transposed=FALSE`.
`BSPARAM` | A BiocSingularParam object specifying the algorithm to use for PCA, if `d` is not `NA`.
`BPPARAM` | A BiocParallelParam object to use for parallel processing.
`assay.type` | A string specifying which assay values to use.
`use.dimred` | A string specifying whether existing values in `reducedDims(x)` should be used.

### Value

A graph where nodes are cells and edges represent connections between nearest neighbors, see `?makeSNNGraph` for more details.

### Author(s)

Aaron Lun

### See Also

`makeSNNGraph` and `makeKNNGraph`, for the underlying functions that do the work.

See `cluster_walktrap` and related functions in igraph for clustering based on the produced graph.

`clusterCells`, for a more succinct way of performing graph-based clustering.

### Examples

    library(scuttle)
    sce <- mockSCE(ncells=500)
    sce <- logNormCounts(sce)

    g <- buildSNNGraph(sce)
    clusters <- igraph::cluster_fast_greedy(g)$membership
    table(clusters)

    # Any clustering method from igraph can be used:
    clusters <- igraph::cluster_walktrap(g)$membership
    table(clusters)

    # Smaller 'k' usually yields finer clusters:
    g <- buildSNNGraph(sce, k=5)
    clusters <- igraph::cluster_walktrap(g)$membership
    table(clusters)

    # Graph can be built off existing reducedDims results:
    sce <- scater::runPCA(sce)
    g <- buildSNNGraph(sce, use.dimred="PCA")
    clusters <- igraph::cluster_fast_greedy(g)$membership
    table(clusters)

[Package scran version 1.22.1 Index]