ti_embeddr.Rd
Will generate a trajectory using Embeddr.
This method was wrapped inside a container. The original code of this method is available here.
ti_embeddr(ndim = 2L, kernel = "nn", metric = "correlation", nn_pct = 0L, eps = 0L, t = 0L, symmetrize = "mean", measure_type = "unorm", thresh = 0.001, maxit = 10L, stretch = 2L, smoother = "smooth.spline")
ndim  Dimension of the embedded space, default is 2. Domain: U(2, 10). Default: 2. Format: integer. 

kernel  The choice of kernel. 'nn' will give nearest neighbours, 'dist' gives minimum distance and'heat' gives a heat kernel. Discussed in detail in 'Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering',Belkin & Niyogi. Domain: nn, dist, heat. Default: nn. Format: character. 
metric  The metric with which to assess 'closeness' for nearest neighbour selection, one of'correlation' (pearson) or 'euclidean'. Default is 'correlation'. Domain: correlation, euclidean, cosine. Default: correlation. Format: character. 
nn_pct  The percentage of cells to use as tge number of nearest neighbours if kernel == 'nn'. Domain: U(2, 1). Default: 0. Format: numeric. 
eps  Maximum distance parameter if kernel == 'dist'. Domain: U(5, 5). Default: 0. Format: numeric. 
t  "time" for heat kernel if kernel == "heat". Domain: U(5, 5). Default: 0. Format: numeric. 
symmetrize  How to make the adjacency matrix symmetric. Note that
slightlycounterintuitively, node i having node j as a nearest neighbour doesn't
guarantee nodej has node i. There are several ways to get round this;* 
measure_type  Type of laplacian eigenmap, which corresponds to the constraint on the eigenvalue problem. Iftype is 'unorm' (default), then the graph measure used is the identity matrix, while if type is 'norm' then the measureused is the degree matrix. Domain: unorm, norm. Default: unorm. Format: character. 
thresh  Convergence threshold on shortest distances to the curve. Domain: e^U(11.51, 11.51). Default: 0.001. Format: numeric. 
maxit  Maximum number of iterations. Domain: U(0, 50). Default: 10. Format: integer. 
stretch  A factor by which the curve can be extrapolated when points are
projected. Default is 2 (times the last segment length). The default is 0 for

smoother  Choice of smoother. The default is 
A TI method wrapper to be used together with
infer_trajectory
Campbell, K., Ponting, C.P., Webber, C., 2015. Laplacian eigenmaps and principal curves for high resolution pseudotemporal ordering of singlecell RNAseq profiles.