treatInterest: Differential retention test relative to a threshold

Description Usage Arguments Value Author(s) See Also Examples

View source: R/treatInterest.R

Description

Compute a genewise statistical test relative to a fold-change threshold using edgeR package. For more information see glmTreat function in edgeR package.

Usage

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	treatInterest(x, design=c(), silent=TRUE, disp="common", 
		coef=c(), contrast=NULL, lfc=0, ...)

Arguments

x

Object of class SummarizedExperiment.

design

Design matrix.

silent

Whether run 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 glmTreat for more information.

contrast

Numeric vector or matrix specifying contrasts of the linear model coefficients to be tested equal to zero. See glmTreat for more information.

lfc

Numeric scalar i.e. the log fold change threshold.

...

Other parameter settings for the glmFit function in the edgeR package.

Value

All values produced by glmTreat plus the following :

dispersionType

The name of the type of dispersion used.

dispersion

The estimated dispersion values.

Author(s)

Ali Oghabian

See Also

exactTestInterest, qlfInterest, glmInterest

Examples

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group <- getAnnotation(mdsChr22Obj)[,"type"]

#Test retention differentiation across the 3 types of sampels 
# The log fold change threshold is 0
treatRes<- treatInterest(x=mdsChr22Obj, 
	design=model.matrix(~group), silent=TRUE, 
	disp="tagwiseInitTrended", coef=2:3, contrast=NULL, lfc=0)
treatRes

IntEREst documentation built on Nov. 8, 2020, 8:05 p.m.