R/ti_cellrouter.R

In dynverse/dynmethods: A collection of trajectory inference methods

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#' @title CellRouter
#' 
#' @description
#' Will generate a trajectory using
#' [CellRouter](https://doi.org/10.1038/s41467-018-03214-y).
#' 
#' This method was wrapped inside a
#' [container](https://github.com/dynverse/ti_cellrouter).
#' The original code of this method is available
#' [here](https://github.com/edroaldo/cellrouter).
#' 
#' @references Lummertz da Rocha, E., Rowe, R.G., Lundin, V., Malleshaiah, M.,
#' Jha, D.K., Rambo, C.R., Li, H., North, T.E., Collins, J.J., Daley, G.Q., 2018.
#' Reconstruction of complex single-cell trajectories using CellRouter. Nature
#' Communications 9.
#' 
#' @param ndim_pca Number of principal components to compute. Domain: U(2, 100).
#' Default: 20. Format: integer.
#' @param ndim_tsne Number of tsne dimensions to compute. Domain: U(2, 100).
#' Default: 11. Format: integer.
#' @param max_iter Maximal number of tsne iterations. Domain: e^U(4.61, 11.51).
#' Default: 1000. Format: integer.
#' @param cluster_method Method to use for clustering. Domain: {graph.clustering,
#' model.clustering}. Default: graph.clustering. Format: character.
#' @param k_clustering Number of nearest neighbors to build a k-nearest neighbors
#' graph for clustering. Domain: U(2, 1000). Default: 20. Format: integer.
#' @param ndim_pca_clustering Number of PCA dimensions used for k-nearest
#' neighbors graph for clustering. Domain: U(2, 100). Default: 20. Format:
#' integer.
#' @param k_knn Number of nearest neighbors to build a k-nearest neighbors graph
#' for knn. Domain: e^U(0.69, 6.91). Default: 10. Format: integer.
#' @param ndim_pca_knn Number of PCA dimensions used for knn. Domain: U(2, 100).
#' Default: 20. Format: integer.
#' @param sim_type Similarity type for knn. Domain: {jaccard}. Default: jaccard.
#' Format: character.
#' @param distance_method_paths Distance method for paths. Domain: {euclidean,
#' maximum, manhattan, canberra, binary, graph}. Default: graph. Format:
#' character.
#' @param ranks How to rank the paths. Domain: {path_cost, path_flow, rank,
#' length}. Default: rank. Format: character.
#' @param num_cells Trajectories should contain at least num.cells. Domain: U(3,
#' 100). Default: 3. Format: integer.
#' @param neighs The size of the neighborhood in kNN graph used to smoothen
#' kinetic profiles. Domain: U(2, 100). Default: 3. Format: integer.
#' @param perplexity Perplexity parameter for tsne. Domain: U(5, 100). Default:
#' 30. Format: numeric.
#' 
#' @keywords method
#' 
#' @return A TI method wrapper to be used together with
#' \code{\link[dynwrap:infer_trajectories]{infer_trajectory}}
#' @export
ti_cellrouter <- function(
    ndim_pca = 20L,
    ndim_tsne = 11L,
    max_iter = 1000L,
    cluster_method = "graph.clustering",
    k_clustering = 20L,
    ndim_pca_clustering = 20L,
    k_knn = 10L,
    ndim_pca_knn = 20L,
    sim_type = "jaccard",
    distance_method_paths = "graph",
    ranks = "rank",
    num_cells = 3L,
    neighs = 3L,
    perplexity = 30L
) {
  method_choose_backend(
    package_repository = NULL,
    package_name = NULL,
    function_name = NULL,
    package_version = NULL,
    container_id = "dynverse/ti_cellrouter:v0.9.9.01"
  )(
    ndim_pca = ndim_pca,
    ndim_tsne = ndim_tsne,
    max_iter = max_iter,
    cluster_method = cluster_method,
    k_clustering = k_clustering,
    ndim_pca_clustering = ndim_pca_clustering,
    k_knn = k_knn,
    ndim_pca_knn = ndim_pca_knn,
    sim_type = sim_type,
    distance_method_paths = distance_method_paths,
    ranks = ranks,
    num_cells = num_cells,
    neighs = neighs,
    perplexity = perplexity
  )
}