ti_dpt | R Documentation |
Will generate a trajectory using DPT.
This method was wrapped inside a container. The original code of this method is available here.
ti_dpt(
sigma = "local",
distance = "euclidean",
ndim = 20L,
density_norm = TRUE,
n_local = c(5L, 7L),
w_width = 0.1
)
sigma |
Diffusion scale parameter of the Gaussian kernel. A larger sigma
might be necessary if the eigenvalues can not be found because of a singularity
in the matrix. Must a character vector – |
distance |
A character vector specifying which distance metric to use.
Allowed measures are the Euclidean distance (default), the cosine distance
( |
ndim |
Number of eigenvectors/dimensions to return. Domain: U(3, 100). Default: 20. Format: integer. |
density_norm |
Logical. If TRUE, use density normalisation. Default: TRUE. Format: logical. |
n_local |
If sigma == 'local', the |
w_width |
Window width to use for deciding the branch cutoff. Domain: e^U(-9.21, 0.00). Default: 0.1. Format: numeric. |
A TI method wrapper to be used together with
infer_trajectory
Haghverdi, L., Büttner, M., Wolf, F.A., Buettner, F., Theis, F.J., 2016. Diffusion pseudotime robustly reconstructs lineage branching. Nature Methods 13, 845–848.
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