A function to perform a weighted, adaptive smoothing of the gene expression of each cell based on the heterogeneity of its neighbourhood. Heterogeneous neighbourhoods are smoothed less with higher weights given to cells belonging to same initial cluster as the index cell. Homogeneous neighbourhoods are smoothed more with similar weights given to most cells.
Arguments
- spe
SpatialExperiment object containing neighbourhood entropy values of each cell.
- nnCells
a character matrix of NN nearest neighbours - rows are index cells and columns are their nearest neighbours ranging from closest to farthest neighbour. For sort = TRUE, the neighbours belonging to the same initial cluster as the index cell are moved closer to it.
- NN
an integer for the number of neighbouring cells the function should consider. The value must be greater than or equal to 1. Default value is 30.
- kernel
a character for type of distribution to be used. The two valid values are "G" or "E" for Gaussian and exponential distributions, respectively. Default value is "G".
- spread
a numeric value for distribution spread, represented by standard deviation for Gaussian distribution and rate for exponential distribution. Default value is 0.3 for Gaussian distribution. The recommended value is 5 for exponential distribution.
Examples
data(ClustSignal_example)
# requires matrix containing NN nearest neighbour cell labels (nnCells),
# generated using the neighbourDetect() function
spe <- clustSIGNAL::adaptiveSmoothing(spe, nnCells)
#> [1] "Smoothing performed. NN = 30 Kernel = G Spread = 0.3 Time 08:51:39"
spe
#> class: SpatialExperiment
#> dim: 351 1000
#> metadata(0):
#> assays(2): logcounts smoothed
#> rownames(351): Abcc4 Acp5 ... Zfp57 Zic3
#> rowData names(0):
#> colnames(1000): embryo2_Pos29_cell110_z2 embryo2_Pos29_cell117_z2 ...
#> embryo2_Pos50_cell361_z5 embryo2_Pos50_cell372_z2
#> colData names(5): uniqueID sample_id entropy initCluster initSubcluster
#> reducedDimNames(1): PCA
#> mainExpName: NULL
#> altExpNames(0):
#> spatialCoords names(2) : X Y
#> imgData names(1): sample_id