Hotgenes: For Visualizing Differential Expression Analysis

FactoWrapper

R Documentation

FactoMiner wrapper used by Shiny_DE_Viz for PCA/HCPC of samples and genes

Description

FactoMiner wrapper used by Shiny_DE_Viz for PCA/HCPC of samples and genes

Usage

FactoWrapper(
  Output_DEseq2 = NULL,
  biplot = TRUE,
  readouts = 1,
  Top_var = 10,
  ellipse.level = 0.5,
  ellipse.alpha = 0.5,
  habillage_selection = "clust",
  label_sel = c("ind", "var"),
  pointsize = 1,
  labelsize = 1,
  selected_contrast = 1
)

Arguments

`Output_DEseq2`	R object generated by DEseq2_export function
`biplot`	Boolean value. If TRUE (Default), both individuals and variables will be shown on the plot. If FALSE, only individuals will be plotted.
`readouts`	either "rlog" (default) or "vsd" indicating the variance stabilization method preferred for visualization.
`Top_var`	a numeric value indicating the number of top contributing genes to show on the biplot.
`ellipse.level`	numeric value for ellipse size, from 0 to 1.0
`ellipse.alpha`	numeric value for ellipse transparency, from 0 to 1.0.
`habillage_selection`	string indicating the grouping to be shown. Default is "clust", which represents the HCPC ward clusters.
`label_sel`	String indicating if individuals "ind" and variables "var" should be labeled on the biplot.
`pointsize`	numeric value for point size.
`labelsize`	numeric value for label size.
`selected_contrast`	string indicating the DE contrast to be explored.

Value

FactoMiner plot showing HCPC of genes, samples, and conditions

Examples

Example_Hotgenes_dir<-system.file("extdata",
"Example_Hotgenes.Rdata",
package = "Hotgenes", mustWork = TRUE)
load(Example_Hotgenes_dir)
FactoWrapper(Example_Hotgenes)

Rvirgenslane/Hotgenes documentation built on June 15, 2024, 2:16 a.m.