ti_forks: FORKS

In dynverse/dynmethods: A collection of trajectory inference methods

FORKS

Description

Will generate a trajectory using FORKS.

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

Usage

ti_forks(
  norm_function = "median",
  norm_quantile = 75L,
  cum_sum_exp_var = 0.9,
  cluster = c(4L, 10L),
  mapping_type = "Isomap",
  initialization = "kmeans",
  iterMax = 1000L,
  eta = 0.01,
  C = 1L
)

Arguments

norm_function	No description provided by the author. Domain: mean, median, quantile. Default: median. Format: character.
norm_quantile	No description provided by the author. Domain: U(0, 100). Default: 75. Format: numeric.
cum_sum_exp_var	No description provided by the author. Domain: U(0, 1). Default: 0.9. Format: numeric.
cluster	No description provided by the author. Domain: ( U(3, 20), U(3, 20) ). Default: (4, 10). Format: integer_range.
mapping_type	No description provided by the author. Domain: Isomap, MDS, PCA, RandomForest, SpectralEmbedding, LLE_standard, tSNE. Default: Isomap. Format: character.
initialization	No description provided by the author. Domain: kmeans, kmedoids, random. Default: kmeans. Format: character.
iterMax	No description provided by the author. Domain: e^U(4.61, 11.51). Default: 1000. Format: integer.
eta	No description provided by the author. Domain: e^U(-9.21, 4.61). Default: 0.01. Format: numeric.
C	No description provided by the author. Domain: e^U(-9.21, 6.91). Default: 1. Format: numeric.

Value

A TI method wrapper to be used together with infer_trajectory

References

Sharma, M., Li, H., Sengupta, D., Prabhakar, S., Jayadeva, 2017. FORKS: Finding Orderings Robustly using k-means and Steiner trees.

dynverse/dynmethods documentation built on Jan. 18, 2024, 4:44 a.m.