obtainResi: Replace expression levels by the residuals of regression...

In GeneSelectMMD: Gene selection based on the marginal distributions of gene profiles that characterized by a mixture of three-component multivariate distributions

Description

Replace expression levels by the residuals of regression analysis in which predictor of interest is not in the regression model. The purpose of this function is to remove potential confounding factors.

Usage

obtainResi(es, fmla)

Arguments

es	An ExpressionSet object.
fmla	A formula object that specifies the covariates of the linear regression model. The variable of interest should not be included. No response variable should be specified in fmla since the response variable is always the expression level. See function lmFit of R Bioconductor package limma.

Details

To remove confounding effects, we can replace the expression level by the residuals of a linear regression model with response variable the expression level and covariates the potential confounders. The functions lmFit and eBayes will be used to obtain regression coefficients.

Value

An ExpressionSet object with expression levels replaced by residuals of linear regression analysis.

Note

The number of arrays of the returned ExpressionSet object might be smaller than that of the original ExpressionSet object, due to missing values in covariates.

Author(s)

Jarrett Morrow [e-mail], Weiliang Qiu [e-mail], Wenqing He [e-mail], Xiaogang Wang [e-mail], Ross Lazarus [e-mail]

GeneSelectMMD documentation built on Nov. 8, 2020, 6:48 p.m.