getResidPerGene: Row-by-Row Linear-Model Residuals for Gene Expression (or...
In GSEAlm: Linear Model Toolset for Gene Set Enrichment Analysis

Description Usage Arguments Details Value Author(s) See Also Examples

View source: R/lmpergene.R

This produces residuals of an identical linear model applied to each row of a gene expression matrix (or similar dataset). Computation speed is achieved via straightforward matrix algebra. Most commonly-used residual types are available.

1	getResidPerGene(lmobj, type = "extStudent")

`lmobj`	An object produced by function `lmPerGene`.
`type`	A string indicating the type of residual requeseted (defaults to externally-Studentized).

Types of residuals now available:

"response": Response residuals, observed minus fitted
"normalized": Response residuals divided by the estimated residual S.E.
"intStudent": Internally Studentized residuals, often referred to as "Standardized"
default: Externally Studentized residuals, which can be used directly for outlier identification

Returns a instance of ExpressionSet where the expression matrix contains the residuals. The phenoData are inherited from lmobj$eS.

Robert Gentleman, Assaf Oron

lmPerGene, resplot,dfbetasPerGene,influence.measures

data(sample.ExpressionSet)
lm1 = lmPerGene(sample.ExpressionSet,~sex)
r1 = getResidPerGene(lm1)
### now a boxplot of all residuals by sample
resplot(resmat=exprs(r1),fac=sample.ExpressionSet$sex)
### This plot is not very informative because of some gross outliers;
### try this instead
resplot(resmat=exprs(r1),fac=sample.ExpressionSet$sex,lims=c(-5,5))