methods.RdGet and set methods for Milo object slots. Generally speaking these methods are used internally, but they allow the user to assign their own externally computed values - should be used with caution.
In the following descriptions x is always a Milo object.
graph(x):Returns an igraph object representation of the
KNN-graph, with number of vertices equal to the number of single-cells.
nhoodDistances(x):Returns a list of sparse matrix of cell-to-cell distances
between nearest neighbours, one list entry per neighbourhood. Largely used internally for computing the k-distance
weighting in graphSpatialFDR.
nhoodCounts(x):Returns a NxM sparse matrix of cell counts in
each of N neighbourhoods with respect to the M experimental samples defined.
nhoodExpression(x):Returns a GxN matrix of gene expression values.
nhoodIndex(x):Returns a list of the single-cells that are the neighbourhood indices.
nhoodReducedDim(x):Returns an NxP matrix of reduced dimension positions. Either
generated by projectNhoodExpression(x) or by providing an NxP matrix (see
setter method below).
nhoods(x):Returns a list of N neighbourhoods and constiuent single-cells.
nhoodGraph(x):Returns an igraph object representation of the
graph of neighbourhoods, with number of vertices equal to the number of neighbourhoods.
nhoodAdjacency(x):Returns a matrix of N by N neighbourhoods with entries
of 1 where neighbourhods share cells, and 0 elsewhere.
In the following descriptions x is always a Milo object.
graph(x) <- value:Populates the graph slot with value -
this should be a valid graph representation in either igraph or list format.
nhoodDistances(x) <- value:Replaces the internally comptued neighbourhood distances. This is normally computed internally during graph building, but can be defined externally. Must be a list with one entry per neighbourhood containing the cell-to-cell distances for the cells within that neighbourhood.
nhoodCounts(x) <- value:Replaces the neighbourhood counts matrix.
This is normally computed and assigned by countCells, however, it can also be user-defined.
nhoodExpression(x) <- value:Replaces the nhoodExpression slot. This is calculated
internally by calcNhoodExpression, which calculates the mean expression. An alternative
summary function can be used to assign an alternative in this way.
nhoodIndex(x) <- value:Replaces the list of neighbourhood indices. This is provided
purely for completeness, and is usually only set internally in makeNhoods.
nhoodReducedDim(x) <- value:Replaces the reduced dimensional representation or projection of neighbourhoods. This can be useful for externally computed projections or representations.
nhoods(x) <- value:Replaces the neighbourhoods. Generally use of this function is discouraged, however, it may be useful for users to define their own bespoke neighbourhoods by some means.
nhoodGraph(x) <- value:Populates the nhoodGraph slot with value -
this should be a valid graph representation in either igraph or list format.
nhoodAdjacency(x) <- value:Populates the nhoodAdjacency slot with value -
this should be a N by N matrix with elements denoting which neighbourhoods share cells
A collection of non-getter and setter methods that operate on Milo objects.
show(x):Prints information to the console regarding the Milo object.
#> 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(0): #> nhoodIndex names(1): 0 #> nhoodExpression dimension(2): 1 1 #> nhoodReducedDim names(0): #> nhoodGraph names(0): #> nhoodAdjacency dimension(0):