`buildGraph.Rd`

This function is borrowed from the old buildKNNGraph function in scran. Instead of returning an igraph object it populates the graph and distance slots in a Milo object. If the input is a SingleCellExperiment object or a matrix then it will return a de novo Milo object with the same slots filled.

buildGraph( x, k = 10, d = 50, transposed = FALSE, get.distance = FALSE, reduced.dim = "PCA", BNPARAM = KmknnParam(), BSPARAM = bsparam(), BPPARAM = SerialParam() )

x | A matrix, |
---|---|

k | An integer scalar that specifies the number of nearest-neighbours to consider for the graph building. |

d | The number of dimensions to use if the input is a matrix of cells X reduced dimensions. If this is provided, transposed should also be set=TRUE. |

transposed | Logical if the input x is transposed with rows as cells. |

get.distance | A logical scalar whether to compute distances during graph construction. |

reduced.dim | A character scalar that refers to a specific entry in
the |

BNPARAM | refer to |

BSPARAM | refer to |

BPPARAM | refer to |

A `Milo`

object with the graph and distance slots populated.

This function computes a k-nearest neighbour graph. Each graph vertex is a
single-cell connected by the edges between its neighbours. Whilst a
kNN-graph is strictly directed, we remove directionality by forcing all
edge weights to 1; this behaviour can be overriden by providing
`directed=TRUE`

.

If you wish to use an
alternative graph structure, such as a shared-NN graph I recommend you
construct this separately and add to the relevant slot in the
`Milo`

object.

library(SingleCellExperiment) ux <- matrix(rpois(12000, 5), ncol=200) vx <- log2(ux + 1) pca <- prcomp(t(vx)) sce <- SingleCellExperiment(assays=list(counts=ux, logcounts=vx), reducedDims=SimpleList(PCA=pca$x)) milo <- Milo(sce) milo <- buildGraph(milo, d=30, transposed=TRUE)#>milo#> class: Milo #> dim: 60 200 #> metadata(0): #> assays(2): counts logcounts #> rownames: NULL #> rowData names(0): #> colnames: NULL #> colData names(0): #> reducedDimNames(1): PCA #> spikeNames(0): #> altExpNames(0): #> nhoods dimensions(1): 0 #> nhoodCounts dimensions(2): 1 1 #> nhoodDistances dimension(1): 0 #> graph names(1): graph #> nhoodIndex names(1): 0 #> nhoodExpression dimension(2): 1 1 #> nhoodReducedDim names(0): #> nhoodGraph names(0): #> nhoodAdjacency dimension(0):