runDGEmods: Perform differential analysis between subgroups at each...

In montilab/K2Taxonomer: Creating annotated submodules of high-throughput data through recursive partitioning

Perform differential analysis between subgroups at each partition

Description

Adds differential analysis results to the output of K2tax().

Usage

runDGEmods(
  K2res,
  DGEmethod = NULL,
  DGEexpThreshold = NULL,
  vehicle = NULL,
  variables = NULL,
  block = NULL,
  logCounts = NULL
)

Arguments

DGEmethod	Character. Method for running differential gene expression analyses. Use one of either 'limma' (default) or 'mast'.
DGEexpThreshold	Numeric. A value between 0 and 1 indicating for filtering lowly expressed genes for partition-specific differential gene expression. Proportion of observations with counts > 0 in at least one subgroup at a specific partition.
vehicle	The value in the cohort variable that contains the ID of observation to use as control. Default NULL if no vehicle to be used.
variables	Character. Columns in meta data of 'object' to control for in differential analyses.
block	Character. Block parameter in limma for modeling higherarchical data structure, such as multiple observations per individual.
logCounts	Logical. Whether or not expression values are log-scale counts or log normalized counts from RNA-seq. Default is TRUE.

Value

An object of class K2.

References

\insertRef

reed_2020K2Taxonomer \insertReflimmaK2Taxonomer \insertRefbhK2Taxonomer

montilab/K2Taxonomer documentation built on April 5, 2025, 3:58 a.m.