ti_scoup: SCOUP

In dynverse/dynmethods: A collection of trajectory inference methods

SCOUP

Description

Will generate a trajectory using SCOUP.

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

Usage

ti_scoup(
  ndim = 2L,
  max_ite1 = 100L,
  max_ite2 = 100L,
  alpha = c(0.1, 100),
  t = c(0.001, 2),
  sigma_squared = 0.1,
  thresh = 0.01
)

Arguments

ndim	Number of pca dimensions. Domain: U(2, 20). Default: 2. Format: integer.
max_ite1	Upper bound of EM iteration (without pseudo-time optimization). Domain: e^U(0.69, 8.52). Default: 100. Format: integer.
max_ite2	Upper bound of EM iteration (including pseudo-time optimization). Domain: e^U(0.69, 13.12). Default: 100. Format: integer.
alpha	Bounds of alpha. Domain: ( e^U(-6.91, 2.30), e^U(-6.91, 2.30) ). Default: (0.1, 100). Format: numeric_range.
t	Bounds of pseudo-time. Domain: ( e^U(-11.51, 0.00), e^U(-11.51, 0.00) ). Default: (0.001, 2). Format: numeric_range.
sigma_squared	Lower bound of sigma squared. Domain: e^U(-6.91, 2.30). Default: 0.1. Format: numeric.
thresh	Threshold. Domain: e^U(-4.61, 2.30). Default: 0.01. Format: numeric.

Value

A TI method wrapper to be used together with infer_trajectory

References

Matsumoto, H., Kiryu, H., 2016. SCOUP: a probabilistic model based on the Ornstein–Uhlenbeck process to analyze single-cell expression data during differentiation. BMC Bioinformatics 17.

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