treatInterest {IntEREst} | R Documentation

## Differential retention test relative to a threshold

### 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

    	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

    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

[Package IntEREst version 1.2.2 Index]