getPCAFunc: Get principal components of arrays

Description Usage Arguments Value Author(s) Examples

View source: R/plotFuncs.R

Description

Get principal components of arrays.

Usage

1
2
3
4
5
6
getPCAFunc(es, 
           labelVariable = "subjID", 
            hybName = "Hybridization_Name",
           requireLog2 = TRUE,
           corFlag = FALSE
)

Arguments

es

An ExpressionSet object

labelVariable

A character string. The name of a phenotype data variable use to label the arrays in the boxplots. By default, labelVariable = "subjID" which is equivalent to labelVariable = "Hybridization_Name".

hybName

character string. indicating the phenotype variable Hybridization_Name.

requireLog2

logical. requiredLog2=TRUE indicates probe expression levels will be log2 transformed. Otherwise, no transformation will be performed.

corFlag

logical. Indicating if correlation matrix (corFlag=TRUE) or covariance (corFlag=FALSE) is used to obtain principal components.

Value

A list with 3 elements:

es.s

An ExpressionSet object with the arrays sorted according to Batch_Run_Date, Chip_Barcode, and Chip_Address

pcs

An object returned by the function prcomp of the R package stats. It contans the following components. sdev (the square roots of the eigenvalues of the covariance/correlation matrix); rotation (a matrix whose columns contain the eigenvectors); x (a matrix whose columns contain principal components); center (the centering used or FALSE); scale (the scale used or FALSE)

requireLog2

logical. The same value as the input requireLog2.

Author(s)

Weiliang Qiu <stwxq@channing.harvard.edu>, Brandon Guo <brandowonder@gmail.com>, Christopher Anderson <christopheranderson84@gmail.com>, Barbara Klanderman <BKLANDERMAN@partners.org>, Vincent Carey <stvjc@channing.harvard.edu>, Benjamin Raby <rebar@channing.harvard.edu>

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
    # generate simulated data set from conditional normal distribution
    set.seed(1234567)
    es.sim = genSimData.BayesNormal(nCpGs = 100, 
      nCases = 20, nControls = 20,
      mu.n = -2, mu.c = 2,
      d0 = 20, s02 = 0.64, s02.c = 1.5, testPara = "var",
      outlierFlag = FALSE, 
      eps = 1.0e-3, applier = lapply) 
    print(es.sim)

    pca.obj = getPCAFunc(es = es.sim, 
               labelVariable = "subjID", 
               hybName = "memSubj",
               requireLog2 = FALSE,
               corFlag = FALSE
    )

iCheck documentation built on Nov. 8, 2020, 11:09 p.m.