WGCNA: standardScreeningNumericTrait – R documentation

Pricing

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

Get Started for Free

Documentation

WGCNA

standardScreeningNumericTrait

Standard screening for numeric traits

Description

Standard screening for numeric traits based on Pearson correlation.

Usage

standardScreeningNumericTrait(datExpr, yNumeric, corFnc = cor,
                              corOptions = list(use = 'p'),
                              alternative = c("two.sided", "less", "greater"),
                              qValues = TRUE,
                              areaUnderROC = TRUE)

Arguments

`datExpr`	data frame containing expression data (or more generally variables to be screened), with rows corresponding to samples and columns to genes (variables)
`yNumeric`	a numeric vector giving the trait measurements for each sample
`corFnc`	correlation function. Defaults to Pearson correlation but can also be `bicor`.
`corOptions`	list specifying additional arguments to be passed to the correlation function given by `corFnc`.
`alternative`	alternative hypothesis for the correlation test
`qValues`	logical: should q-values be calculated?
`areaUnderROC`	logical: should are under the receiver-operating curve be calculated?

Details

The function calculates the correlations, associated p-values, area under the ROC, and q-values

Value

Data frame with the following components:

`ID`	Gene (or variable) identifiers copied from `colnames(datExpr)`
`cor`	correlations of all genes with the trait
`Z`	Fisher Z statistics corresponding to the correlations
`pvalueStudent`	Student p-values of the correlations
`qvalueStudent`	(if input `qValues==TRUE`) q-values of the correlations calculated from the p-values
`AreaUnderROC`	(if input `areaUnderROC==TRUE`) area under the ROC
`nPresentSamples`	number of samples present for the calculation of each association.

Author(s)

Steve Horvath