treatInterest: Differential retention test relative to a threshold
In IntEREst: Intron-Exon Retention Estimator

Description Usage Arguments Value Author(s) See Also Examples

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

1 2	treatInterest(x, design=c(), silent=TRUE, disp="common", coef=c(), contrast=NULL, lfc=0, ...)

`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.

All values produced by glmTreat plus the following :

`dispersionType`	The name of the type of dispersion used.
`dispersion`	The estimated dispersion values.

Ali Oghabian

exactTestInterest, qlfInterest, glmInterest

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