ti_scoup: SCOUP

Description Usage Arguments Value References

Description

Will generate a trajectory using SCOUP.

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

Usage

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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 July 6, 2019, 11:30 a.m.