glmInterest: generalized linear model likelihood ratio tests

View source: R/glmInterest.R

glmInterestR Documentation

generalized linear model likelihood ratio tests

Description

Compute generalized linear model likelihood ratio tests using edgeR package. For more information see glmfit and glmLRT() functions in edgeR package.

Usage

	glmInterest(x, design=c(), silent=TRUE, disp="common", 
		coef=c(), contrast=NULL, ...)

Arguments

x

Object of type SummarizedExperiment.

design

Design matrix.

silent

Whether run the function silently, i.e. without printing the top differential expression tags. Default is TRUE.

disp

The method of estimating the dispersion in the data. Available options are: "common", "trended", "tagwiseInitCommon" and "tagwiseInitTrended". It is also possible to assign a number.

coef

Integer or character vector indicating which coefficients of the linear model are to be tested equal to zero. See glmLRT() in edgeR for more information.

contrast

Numeric vector or matrix specifying contrasts of the linear model coefficients to be tested equal to zero. See glmLRT() in edgeR for more information.

...

Other parameter settings for the glmLRT() function in the edgeR package.

Value

All values produced by glmLRT in edgeR package plus following:

dispersionType

The name of the type of dispersion used.

dispersion

The estimated dispersion values.

Author(s)

Ali Oghabian

See Also

exactTestInterest, qlfInterest, treatInterest

Examples


#Test retention differentiation across the 3 types of sampels
group <- getAnnotation(mdsChr22Obj)[,"type"]
glmRes<- glmInterest(x=mdsChr22Obj, 
	design=model.matrix(~group), silent=TRUE, 
	disp="tagwiseInitTrended", coef=2:3, contrast=NULL)


gacatag/IntEREst documentation built on July 29, 2024, 1:12 a.m.