MFA

Will generate a trajectory using MFA.

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

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.