arseq.pca.plot: Principal Component Analysis

In ajitjohnson/arseq: Automated RNA Sequencing Analysis Pipeline

Description

Plots any two specified principal components. By default it plots the first two principal components.

Usage

arseq.pca.plot(
  dds,
  intgroup = "arseq.group",
  ntop = 500,
  pc.a = 1,
  pc.b = 2,
  returnData = FALSE
)

Arguments

dds	DESeq2 object
intgroup	interesting groups: a character vector of names in colData(x) to use for grouping.
ntop	number of top genes to use for principal components, selected by highest row variance
pc.a	numeric: Defines the first principal component. Default:1
pc.b	numeric: Defines the second principal component.Default:2
returnData	should the function only return the data.frame of 'pc.a' and 'pc.b' with intgroup covariates for custom plotting (default is FALSE)

Value

ggplot of the two selected principal components

Examples

## Not run: 
pca.plot <- arseq.pca.plot (example_dds, intgroup="treatment")

## End(Not run)

ajitjohnson/arseq documentation built on Oct. 28, 2021, 3:53 a.m.