runDiffusionMapsExtension | R Documentation |
This function takes two snap objects - one for reference dataset and one for query dataset and computes the diffusion maps embedding for the query dataset by projecting the query cells into the pre-computed diffusion.
runDiffusionMapsExtension(obj1, obj2, input.mat = c("bmat", "pmat"))
obj1 |
A snap obj for reference dataset |
obj2 |
A snap obj for query dataset |
input.mat |
Input matrix c("bmat", "pmat"). |
The computational complexity of diffusion maps algorithm exhibits quadratic growth with the increase of cells, making it infeasible for large-scale datasets. To overcome this limitation, we apply Nystrom landmark diffusion map algorithm to efficiently generate the low-dimension embedding for large-scale dataset. A practical Nystrom landmark diffusion map algorithm project the query dataset onto the low-dimensional embedding space as learned from the refernce dataset to create a embedding space for query cells.
data(demo.sp); demo.sp = makeBinary(demo.sp);
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