integrate_variables: Integration of an experiment/ Assay done on many Cell lines/...

In OMICsPCA: An R package for quantitative integration and analysis of multiple omics assays from heterogeneous samples

Description

If an assay (e.g. ChIP-seq for the histone modification H3k9ac) is done on multiple cells/conditions/treatment/time, it might be, sometimes, necessary to integrate or combine them. Such combination may be done by several techniques like Principal Component Analysis (PCA) or Factor Analysis (FA). This function integrates an assay experimented on multiple cells or conditions into many linear combinations using PCA.

Usage

integrate_variables(Assays, name, groups, groupinfo = NULL, ...)

Arguments

Assays	A vector of names of an assays
name	Name of the "MultiAssayExperiment" object containing the assay data
groups	Name of all or subset of groups
groupinfo	output of create_group or similar object containing group information
...	Additional arguments supplied to "PCA()" imported from "FactoMineR"

Value

an object of class "PCA"

Author(s)

Subhadeep Das <[e-mail]>

Examples

PCAlist <- integrate_variables(Assays = c("H2az","H3k4me1",
"H3k9ac"), name = multi_assay,
groups = c("WE","RE"), groupinfo = groupinfo_ext,
scale.unit = FALSE, graph = FALSE)

OMICsPCA documentation built on Nov. 8, 2020, 5:01 p.m.