Milo-methods | R Documentation |
Get 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.
See individual methods for return values
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 sparse matrix of CxN
mapping of C
single-cells toN
neighbourhoods.
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 neighbourhood matrix. 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.
Mike Morgan
example(Milo, echo=FALSE)
show(milo)
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