ti_mfa: MFA

In dynverse/dynmethods: A collection of trajectory inference methods

MFA

Description

Will generate a trajectory using MFA.

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

Usage

ti_mfa(
  iter = 2000L,
  thin = 1L,
  pc_initialise = 1L,
  prop_collapse = 0L,
  scale_input = TRUE,
  zero_inflation = FALSE
)

Arguments

iter	Number of MCMC iterations. Domain: U(20, 5000). Default: 2000. Format: integer.
thin	MCMC samples to thin. Domain: U(1, 20). Default: 1. Format: integer.
pc_initialise	Which principal component to initialise pseudotimes to. Domain: U(1, 5). Default: 1. Format: integer.
prop_collapse	Proportion of Gibbs samples which should marginalise over c. Domain: U(0, 1). Default: 0. Format: numeric.
scale_input	Logical. If true, input is scaled to have mean 0 variance 1. Default: TRUE. Format: logical.
zero_inflation	Logical, should zero inflation be enabled?. Default: FALSE. Format: logical.

Value

A TI method wrapper to be used together with infer_trajectory

References

Campbell, K.R., Yau, C., 2017. Probabilistic modeling of bifurcations in single-cell gene expression data using a Bayesian mixture of factor analyzers. Wellcome Open Research 2, 19.

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