Will generate a trajectory using Mpath.

This method was wrapped inside a container. The original code of this method is available here.

ti_mpath(distMethod = "euclidean", method = "kmeans",
  numcluster = 11L, numcluster_null = TRUE, diversity_cut = 0.6,
  size_cut = 0.05)



The method for calculating dissimilarity between cells. distMethod can be one of "pearson", "kendall", "spearman" or "euclidean". Default is "euclidean". Domain: pearson, kendall, spearman, euclidean. Default: euclidean. Format: character.


Method for distinguishing landmark clusters from non-landmark clusters.method can be "kmeans" or "diversity" or "size" or "diversity_size". When method="diversity", numlm needs to be specified. Default is "diversity_size". Domain: kmeans, diversity, size, diversity_size. Default: kmeans. Format: character.


Number of initial clusters. Domain: U(3, 30). Default: 11. Format: integer.


If TRUE, will automatically select the number of clusters. Default: TRUE. Format: logical.


The cutoff value of diversity for differentiating landmark clusters from non-landmark clusters. The diversity of a landmark cluster must be below this cutoff. Domain: U(0.1, 1). Default: 0.6. Format: numeric.


The cutoff value of size i.e. number of cells for differentiating landmark clusters from non-landmark clusters. The number of cells in a landmark cluster must be greater than this cutoff. Domain: U(0.01, 1). Default: 0.05. Format: numeric.


A TI method wrapper to be used together with infer_trajectory


Chen, J., Schlitzer, A., Chakarov, S., Ginhoux, F., Poidinger, M., 2016. Mpath maps multi-branching single-cell trajectories revealing progenitor cell progression during development. Nature Communications 7.