PomaPCA: Principal Components Analysis

In pcastellanoescuder/POMA: Tools for Omics Data Analysis

Principal Components Analysis

Description

PomaPCA performs a principal components analysis on the given SummarizedExperiment object.

Usage

PomaPCA(
  data,
  center = TRUE,
  scale = TRUE,
  ncomp = 4,
  labels = FALSE,
  ellipse = FALSE,
  load_length = 1
)

Arguments

data	A SummarizedExperiment object.
center	Logical. Indicates whether the variables should be shifted to be zero centered. Default is TRUE.
scale	Logical. Indicates whether the variables should be scaled to have unit variance before the analysis takes place. Default is TRUE.
ncomp	Numeric. Number of components to be included in the results. Default is 4.
labels	Logical. Indicates if sample names should be displayed.
ellipse	Logical. Indicates whether a 95 percent confidence interval ellipse should be displayed in score plot and biplot. Default is FALSE.
load_length	Numeric. Indicates the length of biplot loading arrows. Value between 1 and 2. Default is 1.

Value

A list with results including plots and tables.

Author(s)

Pol Castellano-Escuder

Examples

data("st000336")

st000336 %>% 
  PomaImpute() %>%
  PomaNorm() %>%
  PomaPCA()

pcastellanoescuder/POMA documentation built on March 15, 2024, 10:08 p.m.