fgem_marginal: Run FGEM with a dataframe as input This version of FGEM takes...

In CreRecombinase/FGEM: R package for Functional Genomics using Expectation Maximization (FGEM)

Description

Run FGEM with a dataframe as input This version of FGEM takes a single dataframe with both gene-level bayes factors and gene-level features and returns a dataframe with effect size estimates for every feature (run as univariate)

Usage

fgem_marginal(
  X,
  BF,
  prior_mean = 0.02,
  epsilon = 1e-06,
  max_iter = 150,
  parallel = FALSE,
  log_BF = FALSE,
  ...
)

Arguments

X	feature matrix (must have column names)
BF	vector of bayes factors
verbose	Whether to print debug output

CreRecombinase/FGEM documentation built on July 17, 2020, 5:30 a.m.