methodWrapper.limmaVoom: limma + voom

In jhsiao999/ashbun: Methods and evaluation tools for single cell RNA-seq count data

Description

Implement limma with voom and apply the empirical Bayes method in limma.

Usage

methodWrapper.limmaVoom(counts, condition, pseudocount = 0.5,
  control = list(save_modelFit = FALSE))

Arguments

counts	normalized gene by sample expression count matrix. (CPM)
condition	binary vector of length N indicating sample biological condition.
pseudocount	default .5.
control	List with control arguments, including save_modelFit TRUE to output the complete limmaVoom fit results.
libsize_factors	Numeric vector of scale factors for library sizes. Default NULL multiplies all library sizes by 1.

Value

List with the following objects betahat Estimate effect size of condition for all genes. sebetahat Standard errors of the effect sizes. df Degrees of freedom associated with the effect sizes. pvalue P-values of the effect sizes. fit limmaVoom complete output of the model fit.

Author(s)

Chiaowen Joyce Hsiao

jhsiao999/ashbun documentation built on May 8, 2019, 11:17 p.m.