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ti_recat.R
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ti_recat.R
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######################################### DO NOT EDIT! #########################################
#### This file is automatically generated from data-raw/2-generate_r_code_from_containers.R ####
################################################################################################
#' @title reCAT
#'
#' @description
#' Will generate a trajectory using
#' [reCAT](https://doi.org/10.1038/s41467-017-00039-z).
#'
#' This method was wrapped inside a
#' [container](https://github.com/dynverse/ti_recat).
#' The original code of this method is available
#' [here](https://github.com/tinglab/reCAT).
#'
#' @references Liu, Z., Lou, H., Xie, K., Wang, H., Chen, N., Aparicio, O.M.,
#' Zhang, M.Q., Jiang, R., Chen, T., 2017. Reconstructing cell cycle pseudo
#' time-series via single-cell transcriptome data. Nature Communications 8.
#'
#' @param TSPFold No documentation provided by authors. Domain: U(2, 10). Default:
#' 2. Format: integer.
#' @param beginNum No documentation provided by authors. Domain: U(2, 20).
#' Default: 10. Format: integer.
#' @param endNum No documentation provided by authors. Domain: U(2, 20). Default:
#' 15. Format: integer.
#' @param step_size Determines the number of k to skip in your consensus path, ie
#' ifstep_size = 2, then reCAT would only calculate and merge the paths fork = 12,
#' 14, 16, 18, ..., n-2, n. We recommend step_size of up to a maximum of 5 while
#' preserving the performance of reCAT. Usually a step_size of 2 (by default)
#' would suffice and bigger steps are recommended for larger datasets (>1000
#' cells) in order to reduce computational time. Domain: U(2, 20). Default: 2.
#' Format: integer.
#' @param base_cycle_range . Domain: ( U(5, 10), U(5, 10) ). Default: (6, 9).
#' Format: integer_range.
#' @param max_num No documentation provided by authors. Domain: U(100, 500).
#' Default: 300. Format: integer.
#' @param clustMethod No documentation provided by authors. Domain: {GMM, Pam,
#' Kmeans}. Default: GMM. Format: character.
#'
#' @keywords method
#'
#' @return A TI method wrapper to be used together with
#' \code{\link[dynwrap:infer_trajectories]{infer_trajectory}}
#' @export
ti_recat <- function(
TSPFold = 2L,
beginNum = 10L,
endNum = 15L,
step_size = 2L,
base_cycle_range = c(6L, 9L),
max_num = 300L,
clustMethod = "GMM"
) {
method_choose_backend(
package_repository = NULL,
package_name = NULL,
function_name = NULL,
package_version = NULL,
container_id = "dynverse/ti_recat:v0.9.9.01"
)(
TSPFold = TSPFold,
beginNum = beginNum,
endNum = endNum,
step_size = step_size,
base_cycle_range = base_cycle_range,
max_num = max_num,
clustMethod = clustMethod
)
}