RoarDatasetMultipleAPA-class {roar} | R Documentation

## Class `"RoarDatasetMultipleAPA"`

### Description

RoarDataset - a class to perform 3'UTR shortening analyses

### Objects from the Class

Objects of thiss class should be created using the functions `RoarDatasetMultipleAPA` or `RoarDatasetMultipleAPAFromFiles`, 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. This class is used to allow efficient analyses that allow to study more than one APA site for each gene: internally it uses a `RoarDataset` object that stores PRE/POST counts for all possible alternative APA choices for each gene.

### 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.

`geneCoords`:

  Object of class `"GRangesList"` - private object that represents the exon structures of genes in study.

`apaCoords`:

  Object of class `"GRangesList"` - private object that represents the APA fallin on genes in study.

`fragments`:

  Object of class `"GRangesList"` - private object used to efficiently count reads falling on short and long isoforms.

`prePostDef`:

  Object of class `"list"` - private object representing all possible short and long isoforms.

`roars`:

  Object of class `"list"` - private object with a list of `RoarDataset` objects, each one representing all possible PRE/POST choices for a single gene.

`corrTreatment`:

  `"numeric"` slot - private, integer representing the mean length of reads for the treatment samples.

`corrControl`:

  `"numeric"` slot - private, integer representing the mean length of reads for the control samples.

`paired`:

  `"logical"` slot - private.

`step`:

  `"numeric"` slot - private.

`cores`:

  `"numeric"` slot - private.

### Methods

`countPrePost`

  `signature(rds = "RoarDatasetMultipleAPA", stranded = "logical")`: Counts reads falling over all the possible PRE/POST portions of the given transcripts. WARNING: stranded = TRUE is still unsupported and could give unpredictable results.

`computeRoars`

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

`computePvals`

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

totalResults

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

`fpkmResults`

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

`standardFilter`

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

`pvalueFilter`

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

`cores`

  `signature(rds = "RoarDatasetMultipleAPA")`: 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("RoarDatasetMultipleAPA")

[Package roar version 1.16.0 Index]