View source: R/perform.diffusion.map.R
perform.diffusion.map | R Documentation |
Produces diffusion maps from previous reductions, i.e. PCA. Diffusion maps are known to better represent cellular trajectories in non-linear space
perform.diffusion.map( object, assay, reduction, dims, n.dcs = 15, k = 15, diffmap.name.suffix = "", verbose = FALSE, seed = 1234, ... )
object |
IBRAP S4 class object |
assay |
Character. String containing indicating which assay to use |
reduction |
Character. String defining which reduction to supply to the clustering algorithm. |
dims |
Numerical list. The number of dimensions to use for each reduction. This is supplied as a list respective to the order of reductions. |
n.dcs |
Numerical. The number of diffusion components to produce. Default = 15 |
k |
Numerical. How many neighbours should be found per cell. A higher value tends to be more accurate. Default = 15 |
diffmap.name.suffix |
Character. What should be used as a suffix for diffmap |
samp <- perform.diffusion.map(object = samp, assay = c('SCT','SCRAN','SCANPY'), reduction = 'pca', dims = list(20))
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