dea_MCMCglmm: Mixed-effects univariate differential expression analysis...

In biospi/bayesprot: Bayesian Protein-level Quantification for Proteomics

Description

The model is performed pair-wise across the levels of the 'Condition' in 'data.design'. Default is a standard Student's t-test model.

Usage

dea_MCMCglmm(fit, data = protein_quants(fit),
  data.design = design(fit), condition = "Condition",
  fixed = as.formula(paste("~", condition)), random = NULL,
  residual.welch = TRUE, save.intercept = FALSE, output = "MCMCglmm",
  as.data.table = FALSE, use.moderation = FALSE,
  use.precision = TRUE, dist.mean.func = dist_lst_mcmc,
  dist.var.func = dist_invchisq_mcmc, squeeze.var.func = squeeze_var,
  model.seed = control(fit)$model.seed,
  model.nchain = control(fit)$model.nchain,
  model.nwarmup = control(fit)$model.nwarmup,
  model.thin = control(fit)$model.thin,
  model.nsample = control(fit)$model.nsample)

biospi/bayesprot documentation built on Nov. 9, 2019, 2:40 p.m.