RoarDataset-class {roar} | R Documentation

## Class `"RoarDataset"`

### Description

RoarDataset - a class to perform 3'UTR shortening analyses

### Objects from the Class

Objects of thiss class should be created using the functions `RoarDataset` or `RoarDatasetFromFiles`, ideally the raw `new` method should never be invoked by end users. Then to perform the analysis the user should call, in order: countPrePost, computeRoars, computePvals and one of the methods to format results.

### Slots

`treatmentBams`:

  Object of class `"list"` - a list of GappedAlignment objects for the first condition (by convention it is considered the “treated” condition) in analysis.

`controlBams`:

  Object of class `"list"` - a list of GappedAlignment objects for the second condition (by convention it is considered the “control” condition) in analysis.

`prePostCoords`:

  Object of class `"GRanges"` - represents the APA sites coords, defining "PRE" (last exon coords up until the alternative APA, defining the shorter isoform) and "POST" (from the alternative APA to the “standard” one) regions of the genes.

`postCoords`:

  Object of class `"GRanges"` - private object.

`countsTreatment`:

  Object of class `"RangedSummarizedExperiment"` - private object.

`countsControl`:

  Object of class `"RangedSummarizedExperiment"` - private object.

`pVals`:

  Object of class `"RangedSummarizedExperiment"` - private object.

`paired`:

  `"logical"` slot - private.

`step`:

  `"numeric"` slot - private.

`cores`:

  `"numeric"` slot - private.

`metadata`:

  `"list"` slot - private.

`rowRanges`:

  Object of class `"GRangesORGRangesList"` - private object.

`colData`:

  Object of class `"DataFrame"` - private object.

`assays`:

  Object of class `"Assays"` - private object.

### Extends

Class `"RangedSummarizedExperiment"`, directly.

### Methods

`countPrePost`

  `signature(rds = "RoarDataset", stranded = "logical")`: Counts reads falling over PRE/POST portions of the given transcripts.

`computeRoars`

  `signature(rds = "RoarDataset")`: Computes m/M and roar values for this `RoarDataset` object.

`computePvals`

  `signature(rds = "RoarDataset")`: Computes pvalues (Fisher test) for this `RoarDataset` object.

totalResults

  `signature(rds = "RoarDataset")`: Returns a dataframe with results of the analysis for a `RoarDataset` object.

`fpkmResults`

  `signature(rds = "RoarDataset")`: The last step of a classical Roar analyses: it returns a dataframe containing m/M values, roar values, pvalues and estimates of expression (a measure recalling FPKM).

`countResults`

  `signature(rds = "RoarDataset")`: The last step of a classical Roar analyses: it returns a dataframe containing m/M values, roar values, pvalues and estimates of expression (counts over PRE portions).

`standardFilter`

  `signature(rds = "RoarDataset", fpkmCutoff = "double")`: Returns a dataframe with results of the analysis for a `RoarDataset` object.

`pvalueFilter`

  `signature(rds = "RoarDataset", fpkmCutoff = "double", pvalCutoff = "double")`: ...

`cores`

  `signature(rds = "RoarDataset")`: returns the number of cores used for computation, right now always 1.

### Author(s)

Elena Grassi, PhD student in Biomedical Sciences and Oncology - Dept. of Molecular Biotechnologies and Health Sciences, Molecular Biotechnology Center, Torino

### Examples

    showClass("RoarDataset")

[Package roar version 1.18.0 Index]