glmInterest: generalized linear model likelihood ratio tests

In gacatag/IntEREst: Intron-Exon Retention Estimator

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 Aug. 20, 2023, 6:06 p.m.