ti_monocle_ica: Monocle ICA

In dynverse/dynmethods: A collection of trajectory inference methods

Monocle ICA

Description

Will generate a trajectory using Monocle ICA.

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

Usage

ti_monocle_ica(
  reduction_method = "ICA",
  max_components = 2L,
  norm_method = "log",
  filter_features = TRUE,
  filter_features_mean_expression = 0.1
)

Arguments

reduction_method	A character string specifying the algorithm to use for dimensionality reduction. Domain: ICA. Default: ICA. Format: character.
max_components	The dimensionality of the reduced space. Domain: U(2, 20). Default: 2. Format: integer.
norm_method	Determines how to transform expression values prior to reducing dimensionality. Domain: vstExprs, log, none. Default: log. Format: character.
filter_features	Whether to include monocle feature filtering. Default: TRUE. Format: logical.
filter_features_mean_expression	Minimal mean feature expression, only used when filter_features is set to TRUE. Domain: U(0, 10). Default: 0.1. Format: numeric.

Value

A TI method wrapper to be used together with infer_trajectory

References

Qiu, X., Mao, Q., Tang, Y., Wang, L., Chawla, R., Pliner, H.A., Trapnell, C., 2017. Reversed graph embedding resolves complex single-cell trajectories. Nature Methods 14, 979–982.

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