volcano3D (version 2.0.11)

deseq_2x3: 2 x 3 factor DESeq2 analysis

Description

Experimental function for performing 2x3 factor DESeq2 analyses. Output can be passed to deseq_2x3_polar() and subsequently plotted. Example usage would include comparing gene expression against a binary outcome e.g. response vs non-response, across 3 drugs: the design would be ~ response and group would refer to the medication column in the metadata.

Usage

deseq_2x3(object, design, group, ...)

Value

Returns a list of 3 DESeq2 results objects which can be passed onto deseq_2x3_polar()

Arguments

object

An object of class 'DESeqDataSet' containing full dataset

design

Design formula. The main contrast is taken from the last term of the formula and must be a binary factor.

group

Character value for the column with the 3-way grouping factor within the sample information data colData

...

Optional arguments passed to DESeq().

Examples

if (FALSE) { # rlang::is_installed("DESeq2")

# \donttest{
# Basic DESeq2 set up

  library(DESeq2)
  counts <- matrix(rnbinom(n=3000, mu=100, size=1/0.5), ncol=30)
  rownames(counts) <- paste0("gene", 1:100)
  cond <- rep(factor(rep(1:3, each=5), labels = c('A', 'B', 'C')), 2)
  resp <- factor(rep(1:2, each=15), labels = c('non.responder', 'responder'))
  metadata <- data.frame(drug = cond, response = resp)
  
  # Full dataset object construction
  dds <- DESeqDataSetFromMatrix(counts, metadata, ~response)
  
  # Perform 3x DESeq2 analyses comparing binary response for each drug
  res <- deseq_2x3(dds, ~response, "drug")
  
  # Generate polar object
  obj <- deseq_2x3_polar(res)
  
  # 2d plot
  radial_plotly(obj)
  
  # 3d plot
  volcano3D(obj)
# }
}